diff --git a/R/bcanz.R b/R/bcanz.R index fc27ee0f2..e48483db0 100644 --- a/R/bcanz.R +++ b/R/bcanz.R @@ -70,7 +70,7 @@ ssd_fit_bcanz <- function(data, left = "Conc") { #' ssd_hc_bcanz(fits, nboot = 100) ssd_hc_bcanz <- function(x, nboot = 10000, delta = 10, min_pboot = 0.9) { ssd_hc(x, - percent = c(1, 5, 10, 20), + proportion = c(0.01, 0.05, 0.1, 0.2), ci = TRUE, level = 0.95, nboot = nboot, diff --git a/R/data.R b/R/data.R index 962b76f82..2ccfbbc92 100644 --- a/R/data.R +++ b/R/data.R @@ -17,7 +17,7 @@ #' A data frame of the predictions based on 1,000 bootstrap iterations. #' #' \describe{ -#' \item{percent}{The percent of species affected (int).} +#' \item{proportion}{The proportion of species affected (int).} #' \item{est}{The estimated concentration (dbl).} #' \item{se}{The standard error of the estimate (dbl).} #' \item{lcl}{The lower confidence limit (dbl).} diff --git a/R/exposure.R b/R/exposure.R index 5f766d6a2..893d8ac33 100644 --- a/R/exposure.R +++ b/R/exposure.R @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -#' Percent Exposure +#' Proportion Exposure #' #' Calculates average proportion exposed based on log-normal distribution of concentrations. #' diff --git a/R/ggplot.R b/R/ggplot.R index 6c94c03eb..1f04c5b22 100644 --- a/R/ggplot.R +++ b/R/ggplot.R @@ -164,7 +164,7 @@ geom_hcintersect <- function(mapping = NULL, #' @export #' @examples #' gp <- ggplot2::ggplot(boron_pred) + -#' geom_xribbon(ggplot2::aes(xmin = lcl, xmax = ucl, y = percent)) +#' geom_xribbon(ggplot2::aes(xmin = lcl, xmax = ucl, y = proportion)) geom_xribbon <- function(mapping = NULL, data = NULL, stat = "identity", diff --git a/R/hc-burrlioz.R b/R/hc-burrlioz.R index 7a128ca76..61b6431fe 100644 --- a/R/hc-burrlioz.R +++ b/R/hc-burrlioz.R @@ -25,13 +25,25 @@ #' ssd_hc_burrlioz(fit) #' #' @export -ssd_hc_burrlioz <- function(x, percent = 5, ci = FALSE, level = 0.95, nboot = 1000, +ssd_hc_burrlioz <- function(x, percent, proportion = 0.05, ci = FALSE, level = 0.95, nboot = 1000, min_pboot = 0.99, parametric = FALSE) { lifecycle::deprecate_warn("0.3.5", "ssd_hc_burrlioz()", "ssd_hc()") chk_s3_class(x, "fitburrlioz") + + if(lifecycle::is_present(percent)) { + lifecycle::deprecate_soft("1.0.6.9009", "ssd_hc(percent)", "ssd_hc(proportion)", id = "hc") + chk_vector(percent) + chk_numeric(percent) + chk_range(percent, c(0, 100)) + proportion <- percent / 100 + } + + chk_vector(proportion) + chk_numeric(proportion) + chk_range(proportion) ssd_hc(x, - percent = percent, ci = ci, level = level, + proportion = proportion, ci = ci, level = level, nboot = nboot, min_pboot = min_pboot, parametric = parametric ) } diff --git a/R/hc.R b/R/hc.R index 909b12d8d..6139df633 100644 --- a/R/hc.R +++ b/R/hc.R @@ -15,7 +15,7 @@ #' Hazard Concentrations for Species Sensitivity Distributions #' #' Calculates concentration(s) with bootstrap confidence intervals -#' that protect specified percentage(s) of species for +#' that protect specified proportion(s) of species for #' individual or model-averaged distributions #' using parametric or non-parametric bootstrapping. #' @@ -37,9 +37,8 @@ #' calculating the weighted arithmetic means of the lower #' and upper confidence limits based on `nboot` samples for each distribution. #' -#' Based on Burnham and Anderson (2002), -#' distributions with an absolute AIC difference greater -#' than a delta of by default 7 have considerably less support (weight < 0.03) +#' Distributions with an absolute AIC difference greater +#' than a delta of by default 7 have considerably less support (weight < 0.01) #' and are excluded #' prior to calculation of the hazard concentrations to reduce the run time. #' @@ -62,7 +61,7 @@ ssd_hc <- function(x, ...) { est <- do.call(fun, args) tibble( dist = dist, - percent = proportion * 100, est = est, + proportion = proportion, est = est, se = NA_real_, lcl = NA_real_, ucl = NA_real_, wt = 1, nboot = 0L, pboot = NA_real_ @@ -74,19 +73,35 @@ ssd_hc <- function(x, ...) { #' @examples #' #' ssd_hc(ssd_match_moments()) -ssd_hc.list <- function(x, percent = 5, ...) { +ssd_hc.list <- function( + x, + percent, + proportion = 0.05, + ...) { chk_list(x) chk_named(x) chk_unique(names(x)) chk_unused(...) + if(lifecycle::is_present(percent)) { + lifecycle::deprecate_soft("1.0.6.9009", "ssd_hc(percent)", "ssd_hc(proportion)", id = "hc") + chk_vector(percent) + chk_numeric(percent) + chk_range(percent, c(0, 100)) + proportion <- percent / 100 + } + + chk_vector(proportion) + chk_numeric(proportion) + chk_range(proportion) + if (!length(x)) { hc <- no_hcp() - hc <- dplyr::rename(hc, percent = "value") + hc <- dplyr::rename(hc, proportion = "value") return(hc) } hc <- mapply(.ssd_hc_dist, x, names(x), - MoreArgs = list(proportion = percent / 100), + MoreArgs = list(proportion = proportion), SIMPLIFY = FALSE ) bind_rows(hc) @@ -100,7 +115,8 @@ ssd_hc.list <- function(x, percent = 5, ...) { #' ssd_hc(fits) ssd_hc.fitdists <- function( x, - percent = 5, + percent, + proportion = 0.05, average = TRUE, ci = FALSE, level = 0.95, @@ -110,20 +126,27 @@ ssd_hc.fitdists <- function( multi_ci = TRUE, weighted = TRUE, parametric = TRUE, - delta = 7, + delta = 9.21, samples = FALSE, save_to = NULL, control = NULL, ... ) { - chk_vector(percent) - chk_numeric(percent) - chk_range(percent, c(0, 100)) chk_unused(...) - proportion <- percent / 100 - + if(lifecycle::is_present(percent)) { + lifecycle::deprecate_soft("1.0.6.9009", "ssd_hc(percent)", "ssd_hc(proportion)", id = "hc") + chk_vector(percent) + chk_numeric(percent) + chk_range(percent, c(0, 100)) + proportion <- percent / 100 + } + + chk_vector(proportion) + chk_numeric(proportion) + chk_range(proportion) + hcp <- ssd_hcp_fitdists( x = x, value = proportion, @@ -142,8 +165,7 @@ ssd_hc.fitdists <- function( save_to = save_to, hc = TRUE) - hcp <- dplyr::rename(hcp, percent = "value") - hcp <- dplyr::mutate(hcp, percent = .data$percent * 100) + hcp <- dplyr::rename(hcp, proportion = "value") hcp } @@ -155,7 +177,8 @@ ssd_hc.fitdists <- function( #' ssd_hc(fit) ssd_hc.fitburrlioz <- function( x, - percent = 5, + percent, + proportion = 0.05, ci = FALSE, level = 0.95, nboot = 1000, @@ -167,15 +190,22 @@ ssd_hc.fitburrlioz <- function( chk_length(x, upper = 1L) chk_named(x) chk_subset(names(x), c("burrIII3", "invpareto", "llogis", "lgumbel")) - chk_vector(percent) - chk_numeric(percent) - chk_range(percent, c(0, 100)) chk_unused(...) + + if(lifecycle::is_present(percent)) { + lifecycle::deprecate_soft("1.0.6.9009", "ssd_hc(percent)", "ssd_hc(proportion)", id = "hc") + chk_vector(percent) + chk_numeric(percent) + chk_range(percent, c(0, 100)) + proportion <- percent / 100 + } + + chk_vector(proportion) + chk_numeric(proportion) + chk_range(proportion) fun <- if(names(x) == "burrIII3") fit_burrlioz else fit_tmb - proportion <- percent / 100 - hcp <- ssd_hcp_fitdists ( x = x, value = proportion, @@ -195,7 +225,6 @@ ssd_hc.fitburrlioz <- function( fix_weights = FALSE, fun = fun) - hcp <- dplyr::rename(hcp, percent = "value") - hcp <- dplyr::mutate(hcp, percent = .data$percent * 100) + hcp <- dplyr::rename(hcp, proportion = "value") hcp } diff --git a/R/hp.R b/R/hp.R index c1af1b252..991c60465 100644 --- a/R/hp.R +++ b/R/hp.R @@ -12,16 +12,16 @@ # See the License for the specific language governing permissions and # limitations under the License. -#' Hazard Percent +#' Hazard Proportion #' -#' Calculates percent of species affected at specified concentration(s) +#' Calculates proportion of species affected at specified concentration(s) #' with quantile based bootstrap confidence intervals for #' individual or model-averaged distributions #' using parametric or non-parametric bootstrapping. #' For more information see the inverse function [`ssd_hc()`]. #' #' @inheritParams params -#' @return A tibble of corresponding hazard percents. +#' @return A tibble of corresponding hazard proportions. #' @seealso [`ssd_hc()`] #' @export #' @examples @@ -31,7 +31,7 @@ ssd_hp <- function(x, ...) { UseMethod("ssd_hp") } -#' @describeIn ssd_hp Hazard Percents for fitdists Object +#' @describeIn ssd_hp Hazard Proportions for fitdists Object #' @export ssd_hp.fitdists <- function( x, @@ -45,7 +45,7 @@ ssd_hp.fitdists <- function( multi_ci = TRUE, weighted = TRUE, parametric = TRUE, - delta = 7, + delta = 9.21, samples = FALSE, save_to = NULL, control = NULL, @@ -79,7 +79,7 @@ ssd_hp.fitdists <- function( } -#' @describeIn ssd_hp Hazard Percents for fitburrlioz Object +#' @describeIn ssd_hp Hazard Proportions for fitburrlioz Object #' @export #' @examples #' diff --git a/R/params.R b/R/params.R index 1c54afedf..d4b199e9d 100644 --- a/R/params.R +++ b/R/params.R @@ -33,7 +33,7 @@ #' Distributions with an absolute AIC difference greater than delta are excluded from the calculations. #' @param digits A whole number specifying the number of significant figures. #' @param dists A character vector of the distribution names. -#' @param hc A count between 1 and 99 indicating the percent hazard concentration (or NULL). +#' @param hc A value between 0 and 1 indicating the proportion hazard concentration (or NULL). #' @param label A string of the column in data with the labels. #' @param left A string of the column in data with the concentrations. #' @param level A number between 0 and 1 of the confidence level of the interval. @@ -70,8 +70,9 @@ #' @param object The object. #' @param parametric A flag specifying whether to perform parametric bootstrapping as opposed to non-parametrically resampling the original data with replacement. #' @param p vector of probabilities. -#' @param percent A numeric vector of percent values to estimate hazard concentrations for. +#' @param percent A numeric vector of percent values to estimate hazard concentrations for. Soft-deprecated for `proportion = 0.05`. #' @param pmix Proportion mixture parameter. +#' @param proportion A numeric vector of proportion values to estimate hazard concentrations for. #' @param pvalue A flag specifying whether to return p-values or the statistics (default) for the various tests. #' @param pred A data frame of the predictions. #' @param q vector of quantiles. diff --git a/R/plot-cdf.R b/R/plot-cdf.R index d57a8cc0a..b9ff4089d 100644 --- a/R/plot-cdf.R +++ b/R/plot-cdf.R @@ -30,14 +30,13 @@ ssd_plot_cdf <- function(x, ...) { #' @examples #' fits <- ssd_fit_dists(ssddata::ccme_boron) #' ssd_plot_cdf(fits) -ssd_plot_cdf.fitdists <- function(x, average = FALSE, delta = 7, ...) { - pred <- ssd_hc(x, percent = 1:99, average = average, delta = delta) +ssd_plot_cdf.fitdists <- function(x, average = FALSE, delta = 9.21, ...) { + pred <- ssd_hc(x, proportion = 1:99/100, average = average, delta = delta) data <- ssd_data(x) cols <- .cols_fitdists(x) linetype <- if (length(unique(pred$dist)) > 1) "dist" else NULL linecolor <- linetype - pred$percent <- round(pred$percent) # not sure why needed ssd_plot( data = data, pred = pred, left = cols$left, right = cols$right, @@ -57,12 +56,11 @@ ssd_plot_cdf.fitdists <- function(x, average = FALSE, delta = 7, ...) { #' lnorm = c(meanlog = 2, sdlog = 2) #' )) ssd_plot_cdf.list <- function(x, ...) { - pred <- ssd_hc(x, percent = 1:99) + pred <- ssd_hc(x, proportion = 1:99/100) data <- data.frame(Conc = numeric(0)) linetype <- if (length(unique(pred$dist)) > 1) "dist" else NULL linecolor <- linetype - pred$percent <- round(pred$percent) # not sure why needed ssd_plot( data = data, pred = pred, diff --git a/R/predict.R b/R/predict.R index 8b301541d..07625aa55 100644 --- a/R/predict.R +++ b/R/predict.R @@ -30,7 +30,8 @@ stats::predict #' predict(fits) predict.fitdists <- function( object, - percent = 1:99, + percent, + proportion = 1:99/100, average = TRUE, ci = FALSE, level = 0.95, @@ -40,13 +41,27 @@ predict.fitdists <- function( multi_ci = TRUE, weighted = TRUE, parametric = TRUE, - delta = 7, + delta = 9.21, control = NULL, ...) { chk_unused(...) + + + if(lifecycle::is_present(percent)) { + lifecycle::deprecate_soft("1.0.6.9009", "ssd_hc(percent)", "ssd_hc(proportion)", id = "hc") + chk_vector(percent) + chk_numeric(percent) + chk_range(percent, c(0, 100)) + proportion <- percent / 100 + } + + chk_vector(proportion) + chk_numeric(proportion) + chk_range(proportion) + ssd_hc( object, - percent = percent, + proportion = proportion, ci = ci, level = level, nboot = nboot, @@ -76,7 +91,8 @@ predict.fitdists <- function( #' predict(fits) predict.fitburrlioz <- function( object, - percent = 1:99, + percent, + proportion = 1:99/100, ci = FALSE, level = 0.95, nboot = 1000, @@ -84,8 +100,21 @@ predict.fitburrlioz <- function( parametric = TRUE, ...) { chk_unused(...) + + if(lifecycle::is_present(percent)) { + lifecycle::deprecate_soft("1.0.6.9009", "ssd_hc(percent)", "ssd_hc(proportion)", id = "hc") + chk_vector(percent) + chk_numeric(percent) + chk_range(percent, c(0, 100)) + proportion <- percent / 100 + } + + chk_vector(proportion) + chk_numeric(proportion) + chk_range(proportion) + ssd_hc(object, - percent = percent, + proportion = proportion, ci = ci, level = level, nboot = nboot, diff --git a/R/ssd-plot.R b/R/ssd-plot.R index 60f322c57..b593882ce 100644 --- a/R/ssd-plot.R +++ b/R/ssd-plot.R @@ -50,7 +50,7 @@ ssd_plot <- function(data, pred, left = "Conc", right = left, label = NULL, shape = NULL, color = NULL, size = 2.5, linetype = NULL, linecolor = NULL, xlab = "Concentration", ylab = "Species Affected", - ci = TRUE, ribbon = FALSE, hc = 5L, shift_x = 3, + ci = TRUE, ribbon = FALSE, hc = 0.05, shift_x = 3, bounds = c(left = 1, right = 1), xbreaks = waiver()) { .chk_data(data, left, right, weight = NULL, missing = TRUE) @@ -61,9 +61,9 @@ ssd_plot <- function(data, pred, left = "Conc", right = left, chk_null_or(linecolor, vld = vld_string) check_names(data, c(unique(c(left, right)), label, shape)) - check_names(pred, c("percent", "est", "lcl", "ucl", unique(c(linetype, linecolor)))) - chk_numeric(pred$percent) - chk_range(pred$percent, c(1, 99)) + check_names(pred, c("proportion", "est", "lcl", "ucl", unique(c(linetype, linecolor)))) + chk_numeric(pred$proportion) + chk_range(pred$proportion) check_data(pred, values = list(est = 1, lcl = c(1, NA), ucl = c(1, NA))) chk_number(shift_x) @@ -74,14 +74,11 @@ ssd_plot <- function(data, pred, left = "Conc", right = left, if (!is.null(hc)) { chk_vector(hc) - chk_whole_numeric(hc) chk_gt(length(hc)) - chk_subset(hc, pred$percent) + chk_subset(hc, pred$proportion) } .chk_bounds(bounds) - pred$percent <- pred$percent / 100 - data <- process_data(data, left, right, weight = NULL) data <- bound_data(data, bounds) data$y <- ssd_ecd_data(data, "left", "right", bounds = bounds) @@ -96,26 +93,26 @@ ssd_plot <- function(data, pred, left = "Conc", right = left, if (ci) { if (ribbon) { - gp <- gp + geom_xribbon(data = pred, aes(xmin = !!sym("lcl"), xmax = !!sym("ucl"), y = !!sym("percent")), alpha = 0.2) + gp <- gp + geom_xribbon(data = pred, aes(xmin = !!sym("lcl"), xmax = !!sym("ucl"), y = !!sym("proportion")), alpha = 0.2) } else { gp <- gp + - geom_line(data = pred, aes(x = !!sym("lcl"), y = !!sym("percent")), color = "darkgreen") + - geom_line(data = pred, aes(x = !!sym("ucl"), y = !!sym("percent")), color = "darkgreen") + geom_line(data = pred, aes(x = !!sym("lcl"), y = !!sym("proportion")), color = "darkgreen") + + geom_line(data = pred, aes(x = !!sym("ucl"), y = !!sym("proportion")), color = "darkgreen") } } if (!is.null(linecolor)) { - gp <- gp + geom_line(data = pred, aes(x = !!sym("est"), y = !!sym("percent"), linetype = !!linetype, color = !!linecolor)) + gp <- gp + geom_line(data = pred, aes(x = !!sym("est"), y = !!sym("proportion"), linetype = !!linetype, color = !!linecolor)) } else if (ribbon) { - gp <- gp + geom_line(data = pred, aes(x = !!sym("est"), y = !!sym("percent"), linetype = !!linetype), color = "black") + gp <- gp + geom_line(data = pred, aes(x = !!sym("est"), y = !!sym("proportion"), linetype = !!linetype), color = "black") } else { - gp <- gp + geom_line(data = pred, aes(x = !!sym("est"), y = !!sym("percent"), linetype = !!linetype), color = "red") + gp <- gp + geom_line(data = pred, aes(x = !!sym("est"), y = !!sym("proportion"), linetype = !!linetype), color = "red") } if (!is.null(hc)) { gp <- gp + geom_hcintersect( - data = pred[round(pred$percent * 100) %in% hc, ], - aes(xintercept = !!sym("est"), yintercept = !!sym("percent")) + data = pred[pred$proportion %in% hc, ], + aes(xintercept = !!sym("est"), yintercept = !!sym("proportion")) ) } diff --git a/R/wqg.R b/R/wqg.R index f51ba7bd8..72453332a 100644 --- a/R/wqg.R +++ b/R/wqg.R @@ -38,7 +38,7 @@ #' } ssd_wqg_bc <- function(data, left = "Conc") { fits <- ssd_fit_dists(data, left = left, rescale = FALSE) - ssd_hc(fits, ci = TRUE, delta = 7, nboot = 10000) + ssd_hc(fits, ci = TRUE, nboot = 10000) } diff --git a/data-raw/CCME data.csv b/data-raw/CCME data.csv deleted file mode 100644 index 8b6a197ae..000000000 --- a/data-raw/CCME data.csv +++ /dev/null @@ -1 +0,0 @@ -Chemical,Species,Conc,Reference Boron,Oncorhynchus mykiss,2.1,1 Boron,Ictalurus punctatus,2.4,1 Boron,Micropterus salmoides,4.1,1 Boron,Brachydanio rerio,10,1 Boron,Carassius auratus,15.6,1 Boron,Pimephales promelas,18.3,1 Boron,Daphnia magna,6,1 Boron,Opercularia bimarginata,10,1 Boron,Ceriodaphnia dubia,13.4,1 Boron,Entosiphon sulcatum,15,1 Boron,Chironomus decorus,20,1 Boron,Paramecium caudatum,20,1 Boron,Rana pipiens,20.4,1 Boron,Bufo fowleri,48.6,1 Boron,Bufo americanus,50,1 Boron,Ambystoma jeffersonianum,70.7,1 Boron,Ambystoma maculatum,70.7,1 Boron,Rana sylvatica ,70.7,1 Boron,Elodea canadensis,1,1 Boron,Spirodella polyrrhiza,1.8,1 Boron,Chlorella pyrenoidosa,2,1 Boron,Phragmites australis,4,1 Boron,Chlorella vulgaris,5.2,1 Boron,Selenastrum capricornutum,12.3,1 Boron,Scenedesmus subpicatus,30,1 Boron,Myriophyllum spicatum,34.2,1 Boron,Anacystis nidulans,50,1 Boron,Lemna minor ,60,1 Cadmium,Oncorhynchus mykiss,0.23,2 Cadmium,Salvelinus confluentus,0.83,2 Cadmium,Cottus bairdi,0.96,2 Cadmium,Salmo salar,0.99,2 Cadmium,Acipenser transmont anus,1.14,2 Cadmium,Prosopium williamsoni,1.25,2 Cadmium,Salmo trutta,1.36,2 Cadmium,Salvelinus fontinalis,2.23,2 Cadmium,Oncorhynchus tshawytscha,2.29,2 Cadmium,Pimephales promelas,2.36,2 Cadmium,Catostomus commersoni,7.75,2 Cadmium,Oncorhynchus kisutch,7.81,2 Cadmium,Salvelinus namaycush,8.03,2 Cadmium,Esox lucius,8.03,2 Cadmium,Daphnia magna,0.05,2 Cadmium,Ceriodaphnia reticulata,0.12,2 Cadmium,Hyalella azteca,0.12,2 Cadmium,Hydra viridissima,0.87,2 Cadmium,Chironomus tentans,0.96,2 Cadmium,Echinogammarus meridionalis,1.3,2 Cadmium,Atyae phyra desmarestii,1.32,2 Cadmium,Gammarus pulex,1.86,2 Cadmium,Daphnia pulex,2.07,2 Cadmium,Ceriodaphnia dubia,4.9,2 Cadmium,Lampsilis siliquoidea,5.12,2 Cadmium,Aeolosoma headleyi,14.7,2 Cadmium,Lymnaea stagnalis,18.9,2 Cadmium,Chironomus riparius,27.1,2 Cadmium,Lymnaea palustris,58.2,2 Cadmium,Rhithrogena hageni,2659,2 Cadmium,Erythemis simplicicollis,48400,2 Cadmium,Pachydiplax longipennis,76500,2 Cadmium,Ambystoma gracile,106,2 Cadmium,Ankistrodesmus falcatus,4.9,2 Cadmium,Pseudokirchneriella subcapitata,19.8,2 Cadmium,Lemna minor,79,2 Chloride,Pimephales promelas Fathead minnow,598,3 Chloride,Salmo trutta fario Brown trout,607,3 Chloride,Oncorhynchus mykiss Rainbow trout,989,3 Chloride,Xenopus laevis African clawed frog,1307,3 Chloride,Rana pipiens Northern leopard frog,3431,3 Chloride,Lampsilis fasciola Wavy-rayed lampmussel (COSEWIC special concern),24,3 Chloride,Epioblasma torulosa rangiana Northern riffleshell mussel (COSEWIC endangered),42,3 Chloride,Musculium securis Fingernail clam,121,3 Chloride,Daphnia ambigua Water flea,259,3 Chloride,Daphnia pulex Water flea,368,3 Chloride,Elliptio complanata Freshwater mussel,406,3 Chloride,Daphnia magna Water flea,421,3 Chloride,Hyalella azteca Amphipod,421,3 Chloride,Ceriodaphnia dubia Water flea,454,3 Chloride,Tubifex tubifex Oligochaete,519,3 Chloride,Villosa delumbis Freshwater mussel,716,3 Chloride,Villosa constricta Freshwater mussel,789,3 Chloride,Lumbriculus variegates Oligochaete,825,3 Chloride,Brachionus calyciflorus,1241,3 Chloride,Lampsilis siliquoidea Freshwater mussel,1474,3 Chloride,Gammarus pseudopinmaeus Amphipod,2000,3 Chloride,Physa sp. Snail,2000,3 Chloride,Stenonema modestum Mayfly,2047,3 Chloride,Chironomus tentans Midge,2316,3 Chloride,Lemna minor Duckweed,1171,3 Chloride,Chlorella minutissimo Algae,6066,3 Chloride,Chlorella zofingiensis Algae,6066,3 Chloride,Chlorella emersonii Algae,6824,3 Endosulfan,Oncorhynchus mykiss,0.05,4 Endosulfan,Channa punctata,0.24,4 Endosulfan,Pimephales promelas,0.28,4 Endosulfan,Hydra vulgaris,0.06,4 Endosulfan,Hydra viridissima,0.07,4 Endosulfan,Daphnia magna,14.1,4 Endosulfan,Ceriodaphnia dubia,14.1,4 Endosulfan,Moinodaphnia macleayi,28.3,4 Endosulfan,Daphnia cephalata,113.14,4 Endosulfan,Brachionus calyciflorus,1000,4 Endosulfan,Pseudokirchneriell a subcapitatum,427.8,4 Endosulfan,Scenedesmus subspicatus,560,4 Glyphosate,O. kisutch,130000,5 Glyphosate,O. mykiss,150000,5 Glyphosate,P. promelas,25700,5 Glyphosate,C. dubia,65000,5 Glyphosate,D. magna,10487,5 Glyphosate,H. azteca,20500,5 Glyphosate,P. columella,3162,5 Glyphosate,A. flosaquae,12000,5 Glyphosate,C. pyrenoidosa,3530,5 Glyphosate,C. vulgaris,4696,5 Glyphosate,L. gibba,1587,5 Glyphosate,M. sibiricum,1474,5 Glyphosate,N. pelliculosa,1800,5 Glyphosate,P. pectinatus,3162,5 Glyphosate,P. subcapitata,10000,5 Glyphosate,S. acutus,2820,5 Glyphosate,S. obliquus,55858,5 Glyphosate,S. quadricauda,1090,5 Uranium,O. mykiss,350,6 Uranium,P. promelas,1040,6 Uranium,E. luius,2550,6 Uranium,S. namaycush,13400,6 Uranium,C. commersoni,14300,6 Uranium,H. azteca,12,6 Uranium,C. dubia,73,6 Uranium,S. serrulatus,480,6 Uranium,D. magna,530,6 Uranium,C. tentans,930,6 Uranium,P.subcapitata,40,6 Uranium,L. minor,3100,6 Uranium,C. erosa,172,6 Silver,O. mykiss,0.24,7 Silver,L. gibba,0.63,7 Silver,C. dubia,0.78,7 Silver,P. promelas,0.83,7 Silver,I. punctatus,1.9,7 Silver,D. magna,2.12,7 Silver,H. azteca,4,7 Silver,C. tentans,13,7 Silver,M. salmoides,23,7 ,,, \ No newline at end of file diff --git a/data-raw/README.md b/data-raw/README.md deleted file mode 100644 index a1493a3c0..000000000 --- a/data-raw/README.md +++ /dev/null @@ -1,15 +0,0 @@ -## Data Sources - -The `CCME data.csv` data file is provided—with permission to use and redistribute—by the [Canadian Council of the Ministers of the Environment (CCME)](http://ceqg-rcqe.ccme.ca/en/index.html). - -The citations and data sources are as follows: - -- Boron: [Canadian Council of Ministers of the Environment. 2009. Canadian water quality guidelines for the protection of aquatic life: Boron. In: Canadian environmental quality guidelines, 2009, Canadian Council of Ministers of the Environment, Winnipeg.](http://ceqg-rcqe.ccme.ca/download/en/324/) -- Cadmium: [Canadian Council of Ministers of the Environment. 2014. Canadian water quality guidelines for the protection of aquatic life: Cadmium. In: Canadian environmental quality guidelines, 1999, Canadian Council of Ministers of the Environment, Winnipeg.](http://ceqg-rcqe.ccme.ca/download/en/148/) -- Chloride: [Canadian Council of Ministers of the Environment. 2011. Canadian water quality guidelines for the protection of aquatic life: Chloride. In: Canadian environmental quality guidelines, 1999, Canadian Council of Ministers of the Environment, Winnipeg. ](http://ceqg-rcqe.ccme.ca/download/en/337/) -- Endosulfan: [Canadian Council of Ministers of the Environment. 2010. Canadian water quality guidelines for the protection of aquatic life: Endosulfan. In: Canadian environmental quality guidelines, 1999, Canadian Council of Ministers of the Environment, Winnipeg.](http://ceqg-rcqe.ccme.ca/download/en/327/) -- Glyphosate: [Canadian Council of Ministers of the Environment. 2012. Canadian water quality guidelines for the protection of aquatic life: Glyphosate. In: Canadian environmental quality guidelines, Canadian Council of Ministers of the Environment, Winnipeg.](http://ceqg-rcqe.ccme.ca/download/en/182/) -- Uranium: [Canadian Council of Ministers of the Environment. 2011. Canadian water quality guidelines for the protection of aquatic life: Uranium. In: Canadian environmental quality guidelines, 1999, Canadian Council of Ministers of the Environment, Winnipeg.](http://ceqg-rcqe.ccme.ca/download/en/328/) -- Silver: [Canadian Council of Ministers of the Environment. 2015. Canadian water quality guidelines for the protection of aquatic life: Silver. In: Canadian environmental quality guidelines, 1999, Canadian Council of Ministers of the Environment, Winnipeg.](http://ceqg-rcqe.ccme.ca/download/en/355/) - - diff --git a/data-raw/data-raw.R b/data-raw/data-raw.R index db1b43195..550ce50d4 100644 --- a/data-raw/data-raw.R +++ b/data-raw/data-raw.R @@ -36,5 +36,5 @@ use_data(dist_data, overwrite = TRUE) fits <- ssd_fit_dists(ssddata::ccme_boron) set.seed(99) -boron_pred <- predict(fits, ci = TRUE) +boron_pred <- predict(fits, ci = TRUE, multi_ci = FALSE) use_data(boron_pred, overwrite = TRUE) diff --git a/data/boron_pred.rda b/data/boron_pred.rda index b07623365..0f010c836 100644 Binary files a/data/boron_pred.rda and b/data/boron_pred.rda differ diff --git a/data/dist_data.rda b/data/dist_data.rda index d0e4ffc22..ba4b4b869 100644 Binary files a/data/dist_data.rda and b/data/dist_data.rda differ diff --git a/man/boron_pred.Rd b/man/boron_pred.Rd index a51fb9033..c27431921 100644 --- a/man/boron_pred.Rd +++ b/man/boron_pred.Rd @@ -5,7 +5,7 @@ \alias{boron_pred} \title{Model Averaged Predictions for CCME Boron Data} \format{ -An object of class \code{tbl_df} (inherits from \code{tbl}, \code{data.frame}) with 99 rows and 10 columns. +An object of class \code{tbl_df} (inherits from \code{tbl}, \code{data.frame}) with 99 rows and 11 columns. } \usage{ boron_pred @@ -15,7 +15,7 @@ A data frame of the predictions based on 1,000 bootstrap iterations. } \details{ \describe{ -\item{percent}{The percent of species affected (int).} +\item{proportion}{The proportion of species affected (int).} \item{est}{The estimated concentration (dbl).} \item{se}{The standard error of the estimate (dbl).} \item{lcl}{The lower confidence limit (dbl).} diff --git a/man/geom_xribbon.Rd b/man/geom_xribbon.Rd index a60908201..93aa2b7c3 100644 --- a/man/geom_xribbon.Rd +++ b/man/geom_xribbon.Rd @@ -70,7 +70,7 @@ Plots the \code{x} interval defined by \code{xmin} and \code{xmax}. } \examples{ gp <- ggplot2::ggplot(boron_pred) + - geom_xribbon(ggplot2::aes(xmin = lcl, xmax = ucl, y = percent)) + geom_xribbon(ggplot2::aes(xmin = lcl, xmax = ucl, y = proportion)) } \seealso{ \code{\link[=ssd_plot_cdf]{ssd_plot_cdf()}} diff --git a/man/params.Rd b/man/params.Rd index 9280e50d6..bfda2b9bd 100644 --- a/man/params.Rd +++ b/man/params.Rd @@ -40,7 +40,7 @@ Distributions with an absolute AIC difference greater than delta are excluded fr \item{dists}{A character vector of the distribution names.} -\item{hc}{A count between 1 and 99 indicating the percent hazard concentration (or NULL).} +\item{hc}{A value between 0 and 1 indicating the proportion hazard concentration (or NULL).} \item{label}{A string of the column in data with the labels.} @@ -111,10 +111,12 @@ remove them with a warning.} \item{p}{vector of probabilities.} -\item{percent}{A numeric vector of percent values to estimate hazard concentrations for.} +\item{percent}{A numeric vector of percent values to estimate hazard concentrations for. Soft-deprecated for \code{proportion = 0.05}.} \item{pmix}{Proportion mixture parameter.} +\item{proportion}{A numeric vector of proportion values to estimate hazard concentrations for.} + \item{pvalue}{A flag specifying whether to return p-values or the statistics (default) for the various tests.} \item{pred}{A data frame of the predictions.} diff --git a/man/predict.fitburrlioz.Rd b/man/predict.fitburrlioz.Rd index 98bf07d6f..be7ebec97 100644 --- a/man/predict.fitburrlioz.Rd +++ b/man/predict.fitburrlioz.Rd @@ -6,7 +6,8 @@ \usage{ \method{predict}{fitburrlioz}( object, - percent = 1:99, + percent, + proportion = 1:99/100, ci = FALSE, level = 0.95, nboot = 1000, @@ -18,7 +19,9 @@ \arguments{ \item{object}{The object.} -\item{percent}{A numeric vector of percent values to estimate hazard concentrations for.} +\item{percent}{A numeric vector of percent values to estimate hazard concentrations for. Soft-deprecated for \code{proportion = 0.05}.} + +\item{proportion}{A numeric vector of proportion values to estimate hazard concentrations for.} \item{ci}{A flag specifying whether to estimate confidence intervals (by bootstrapping).} diff --git a/man/predict.fitdists.Rd b/man/predict.fitdists.Rd index bf99e17a3..eaf5405a6 100644 --- a/man/predict.fitdists.Rd +++ b/man/predict.fitdists.Rd @@ -6,7 +6,8 @@ \usage{ \method{predict}{fitdists}( object, - percent = 1:99, + percent, + proportion = 1:99/100, average = TRUE, ci = FALSE, level = 0.95, @@ -16,7 +17,7 @@ multi_ci = TRUE, weighted = TRUE, parametric = TRUE, - delta = 7, + delta = 9.21, control = NULL, ... ) @@ -24,7 +25,9 @@ \arguments{ \item{object}{The object.} -\item{percent}{A numeric vector of percent values to estimate hazard concentrations for.} +\item{percent}{A numeric vector of percent values to estimate hazard concentrations for. Soft-deprecated for \code{proportion = 0.05}.} + +\item{proportion}{A numeric vector of proportion values to estimate hazard concentrations for.} \item{average}{A flag specifying whether to provide model averaged values as opposed to a value for each distribution.} diff --git a/man/ssd_exposure.Rd b/man/ssd_exposure.Rd index 46f81d0be..dca6eb7bc 100644 --- a/man/ssd_exposure.Rd +++ b/man/ssd_exposure.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/exposure.R \name{ssd_exposure} \alias{ssd_exposure} -\title{Percent Exposure} +\title{Proportion Exposure} \usage{ ssd_exposure(x, meanlog = 0, sdlog = 1, nboot = 1000) } diff --git a/man/ssd_hc.Rd b/man/ssd_hc.Rd index f5e0c066d..9d9a8d496 100644 --- a/man/ssd_hc.Rd +++ b/man/ssd_hc.Rd @@ -9,11 +9,12 @@ \usage{ ssd_hc(x, ...) -\method{ssd_hc}{list}(x, percent = 5, ...) +\method{ssd_hc}{list}(x, percent, proportion = 0.05, ...) \method{ssd_hc}{fitdists}( x, - percent = 5, + percent, + proportion = 0.05, average = TRUE, ci = FALSE, level = 0.95, @@ -23,7 +24,7 @@ ssd_hc(x, ...) multi_ci = TRUE, weighted = TRUE, parametric = TRUE, - delta = 7, + delta = 9.21, samples = FALSE, save_to = NULL, control = NULL, @@ -32,7 +33,8 @@ ssd_hc(x, ...) \method{ssd_hc}{fitburrlioz}( x, - percent = 5, + percent, + proportion = 0.05, ci = FALSE, level = 0.95, nboot = 1000, @@ -48,7 +50,9 @@ ssd_hc(x, ...) \item{...}{Unused.} -\item{percent}{A numeric vector of percent values to estimate hazard concentrations for.} +\item{percent}{A numeric vector of percent values to estimate hazard concentrations for. Soft-deprecated for \code{proportion = 0.05}.} + +\item{proportion}{A numeric vector of proportion values to estimate hazard concentrations for.} \item{average}{A flag specifying whether to provide model averaged values as opposed to a value for each distribution.} @@ -87,7 +91,7 @@ A tibble of corresponding hazard concentrations. } \description{ Calculates concentration(s) with bootstrap confidence intervals -that protect specified percentage(s) of species for +that protect specified proportion(s) of species for individual or model-averaged distributions using parametric or non-parametric bootstrapping. } @@ -110,9 +114,8 @@ its weight (so that they sum to \code{nboot}) versus calculating the weighted arithmetic means of the lower and upper confidence limits based on \code{nboot} samples for each distribution. -Based on Burnham and Anderson (2002), -distributions with an absolute AIC difference greater -than a delta of by default 7 have considerably less support (weight < 0.03) +Distributions with an absolute AIC difference greater +than a delta of by default 7 have considerably less support (weight < 0.01) and are excluded prior to calculation of the hazard concentrations to reduce the run time. } diff --git a/man/ssd_hc_burrlioz.Rd b/man/ssd_hc_burrlioz.Rd index 633a32ab8..d9fa361e9 100644 --- a/man/ssd_hc_burrlioz.Rd +++ b/man/ssd_hc_burrlioz.Rd @@ -7,7 +7,8 @@ \usage{ ssd_hc_burrlioz( x, - percent = 5, + percent, + proportion = 0.05, ci = FALSE, level = 0.95, nboot = 1000, @@ -18,7 +19,9 @@ ssd_hc_burrlioz( \arguments{ \item{x}{The object.} -\item{percent}{A numeric vector of percent values to estimate hazard concentrations for.} +\item{percent}{A numeric vector of percent values to estimate hazard concentrations for. Soft-deprecated for \code{proportion = 0.05}.} + +\item{proportion}{A numeric vector of proportion values to estimate hazard concentrations for.} \item{ci}{A flag specifying whether to estimate confidence intervals (by bootstrapping).} diff --git a/man/ssd_hp.Rd b/man/ssd_hp.Rd index 2b555eba3..c5c4f88e1 100644 --- a/man/ssd_hp.Rd +++ b/man/ssd_hp.Rd @@ -4,7 +4,7 @@ \alias{ssd_hp} \alias{ssd_hp.fitdists} \alias{ssd_hp.fitburrlioz} -\title{Hazard Percent} +\title{Hazard Proportion} \usage{ ssd_hp(x, ...) @@ -20,7 +20,7 @@ ssd_hp(x, ...) multi_ci = TRUE, weighted = TRUE, parametric = TRUE, - delta = 7, + delta = 9.21, samples = FALSE, save_to = NULL, control = NULL, @@ -80,10 +80,10 @@ Distributions with an absolute AIC difference greater than delta are excluded fr \item{control}{A list of control parameters passed to \code{\link[stats:optim]{stats::optim()}}.} } \value{ -A tibble of corresponding hazard percents. +A tibble of corresponding hazard proportions. } \description{ -Calculates percent of species affected at specified concentration(s) +Calculates proportion of species affected at specified concentration(s) with quantile based bootstrap confidence intervals for individual or model-averaged distributions using parametric or non-parametric bootstrapping. @@ -91,9 +91,9 @@ For more information see the inverse function \code{\link[=ssd_hc]{ssd_hc()}}. } \section{Methods (by class)}{ \itemize{ -\item \code{ssd_hp(fitdists)}: Hazard Percents for fitdists Object +\item \code{ssd_hp(fitdists)}: Hazard Proportions for fitdists Object -\item \code{ssd_hp(fitburrlioz)}: Hazard Percents for fitburrlioz Object +\item \code{ssd_hp(fitburrlioz)}: Hazard Proportions for fitburrlioz Object }} \examples{ diff --git a/man/ssd_plot.Rd b/man/ssd_plot.Rd index 79b6a72a7..783e33d13 100644 --- a/man/ssd_plot.Rd +++ b/man/ssd_plot.Rd @@ -19,7 +19,7 @@ ssd_plot( ylab = "Species Affected", ci = TRUE, ribbon = FALSE, - hc = 5L, + hc = 0.05, shift_x = 3, bounds = c(left = 1, right = 1), xbreaks = waiver() @@ -54,7 +54,7 @@ ssd_plot( \item{ribbon}{A flag indicating whether to plot the confidence interval as a grey ribbon as opposed to green solid lines.} -\item{hc}{A count between 1 and 99 indicating the percent hazard concentration (or NULL).} +\item{hc}{A value between 0 and 1 indicating the proportion hazard concentration (or NULL).} \item{shift_x}{The value to multiply the label x values by.} diff --git a/man/ssd_plot_cdf.Rd b/man/ssd_plot_cdf.Rd index 9cd6a8ff4..56e5496c1 100644 --- a/man/ssd_plot_cdf.Rd +++ b/man/ssd_plot_cdf.Rd @@ -8,7 +8,7 @@ \usage{ ssd_plot_cdf(x, ...) -\method{ssd_plot_cdf}{fitdists}(x, average = FALSE, delta = 7, ...) +\method{ssd_plot_cdf}{fitdists}(x, average = FALSE, delta = 9.21, ...) \method{ssd_plot_cdf}{list}(x, ...) } diff --git a/paper/figure.R b/paper/figure.R index e74419ab5..9ffb417e5 100644 --- a/paper/figure.R +++ b/paper/figure.R @@ -6,7 +6,7 @@ dists <- ssd_fit_dists(ssddata::ccme_boron) hc <- ssd_hc(dists) gp <- autoplot(dists) + - geom_hcintersect(data = hc, aes(xintercept = est, yintercept = percent/100)) + geom_hcintersect(data = hc, aes(xintercept = est, yintercept = proportion)) print(gp) diff --git a/tests/testthat/_snaps/bcanz/hc_chloride.csv b/tests/testthat/_snaps/bcanz/hc_chloride.csv index be231303a..e94414a81 100644 --- a/tests/testthat/_snaps/bcanz/hc_chloride.csv +++ b/tests/testthat/_snaps/bcanz/hc_chloride.csv @@ -1,5 +1,5 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,1,0.267258,0.110132,0.0373797,0.336421,1,parametric,10,0.8,numeric(0) -average,5,1.25677,0.426673,0.395098,1.58918,1,parametric,10,0.8,numeric(0) -average,10,2.38165,0.729251,1.01781,3.05366,1,parametric,10,0.8,numeric(0) -average,20,4.81004,1.247,2.733,6.16935,1,parametric,10,0.8,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.01,0.267258,0.110132,0.0373797,0.336421,1,parametric,10,0.8,numeric(0) +average,0.05,1.25677,0.426673,0.395098,1.58918,1,parametric,10,0.8,numeric(0) +average,0.1,2.38165,0.729251,1.01781,3.05366,1,parametric,10,0.8,numeric(0) +average,0.2,4.81004,1.247,2.733,6.16935,1,parametric,10,0.8,numeric(0) diff --git a/tests/testthat/_snaps/burrIII3/hc_chloride.csv b/tests/testthat/_snaps/burrIII3/hc_chloride.csv index 511037450..340c2134e 100644 --- a/tests/testthat/_snaps/burrIII3/hc_chloride.csv +++ b/tests/testthat/_snaps/burrIII3/hc_chloride.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,78.2897,66.6679,49.5803,241.121,1,parametric,10,1,"c(`000000001_burrIII3` = 275.866, `000000002_burrIII3` = 68.0712, `000000003_burrIII3` = 69.1215, `000000004_burrIII3` = 87.1669, `000000005_burrIII3` = 99.0681, `000000006_burrIII3` = 75.2955, `000000007_burrIII3` = 49.5406, `000000008_burrIII3` = 121.446, `000000009_burrIII3` = 49.7169, `000000010_burrIII3` = 69.8141)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,78.2897,66.6679,49.5803,241.121,1,parametric,10,1,"c(`000000001_burrIII3` = 275.866, `000000002_burrIII3` = 68.0712, `000000003_burrIII3` = 69.1215, `000000004_burrIII3` = 87.1669, `000000005_burrIII3` = 99.0681, `000000006_burrIII3` = 75.2955, `000000007_burrIII3` = 49.5406, `000000008_burrIII3` = 121.446, `000000009_burrIII3` = 49.7169, `000000010_burrIII3` = 69.8141)" diff --git a/tests/testthat/_snaps/burrIII3/hc_uranium.csv b/tests/testthat/_snaps/burrIII3/hc_uranium.csv index d098f6404..0366c48a6 100644 --- a/tests/testthat/_snaps/burrIII3/hc_uranium.csv +++ b/tests/testthat/_snaps/burrIII3/hc_uranium.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,16.7034,19.9308,4.02109,58.4951,1,parametric,10,1,"c(`000000001_burrIII3` = 64.5764, `000000002_burrIII3` = 5.34432, `000000003_burrIII3` = 7.7973, `000000004_burrIII3` = 4.32216, `000000005_burrIII3` = 10.0636, `000000006_burrIII3` = 10.8304, `000000007_burrIII3` = 5.65714, `000000008_burrIII3` = 37.5486, `000000009_burrIII3` = 4.96084, `000000010_burrIII3` = 3.93368)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,16.7034,19.9308,4.02109,58.4951,1,parametric,10,1,"c(`000000001_burrIII3` = 64.5764, `000000002_burrIII3` = 5.34432, `000000003_burrIII3` = 7.7973, `000000004_burrIII3` = 4.32216, `000000005_burrIII3` = 10.0636, `000000006_burrIII3` = 10.8304, `000000007_burrIII3` = 5.65714, `000000008_burrIII3` = 37.5486, `000000009_burrIII3` = 4.96084, `000000010_burrIII3` = 3.93368)" diff --git a/tests/testthat/_snaps/ggplot/geom_xribbon.png b/tests/testthat/_snaps/ggplot/geom_xribbon.png index 4b3dd3ef7..a6f322a73 100644 Binary files a/tests/testthat/_snaps/ggplot/geom_xribbon.png and b/tests/testthat/_snaps/ggplot/geom_xribbon.png differ diff --git a/tests/testthat/_snaps/gompertz/hc_prob.csv b/tests/testthat/_snaps/gompertz/hc_prob.csv index 90be1fdd9..68637669f 100644 --- a/tests/testthat/_snaps/gompertz/hc_prob.csv +++ b/tests/testthat/_snaps/gompertz/hc_prob.csv @@ -1,5 +1,5 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,0.179431,0.307761,0.0992247,1.2374,1,parametric,100,0.92,"c(`000000001_gompertz` = 0.232636, `000000003_gompertz` = 0.104637, `000000004_gompertz` = 0.546398, `000000005_gompertz` = 0.597141, `000000006_gompertz` = 0.232612, `000000007_gompertz` = 0.260431, `000000008_gompertz` = 0.194922, `000000009_gompertz` = 0.687422, `000000010_gompertz` = 0.158599, `000000011_gompertz` = 0.252416, `000000012_gompertz` = 0.212662, `000000013_gompertz` = 1.32511, `000000014_gompertz` = 0.196367, `000000015_gompertz` = 0.556544, `000000016_gompertz` = 0.542006, `000000017_gompertz` = 0.258814, +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,0.179431,0.307761,0.0992247,1.2374,1,parametric,100,0.92,"c(`000000001_gompertz` = 0.232636, `000000003_gompertz` = 0.104637, `000000004_gompertz` = 0.546398, `000000005_gompertz` = 0.597141, `000000006_gompertz` = 0.232612, `000000007_gompertz` = 0.260431, `000000008_gompertz` = 0.194922, `000000009_gompertz` = 0.687422, `000000010_gompertz` = 0.158599, `000000011_gompertz` = 0.252416, `000000012_gompertz` = 0.212662, `000000013_gompertz` = 1.32511, `000000014_gompertz` = 0.196367, `000000015_gompertz` = 0.556544, `000000016_gompertz` = 0.542006, `000000017_gompertz` = 0.258814, `000000018_gompertz` = 0.467321, `000000019_gompertz` = 0.444488, `000000020_gompertz` = 0.252327, `000000021_gompertz` = 1.00609, `000000022_gompertz` = 0.262124, `000000023_gompertz` = 0.201934, `000000024_gompertz` = 0.221751, `000000025_gompertz` = 0.370771, `000000026_gompertz` = 0.381563, `000000027_gompertz` = 0.587611, `000000028_gompertz` = 0.154166, `000000031_gompertz` = 0.104224, `000000032_gompertz` = 0.249995, `000000033_gompertz` = 0.462125, `000000034_gompertz` = 0.396521, `000000035_gompertz` = 0, `000000036_gompertz` = 0.258785, `000000037_gompertz` = 0.242243, `000000038_gompertz` = 0.347565, `000000039_gompertz` = 0.294371, `000000040_gompertz` = 1.14334, `000000041_gompertz` = 0.135071, `000000042_gompertz` = 0.119921, `000000043_gompertz` = 0.313962, `000000044_gompertz` = 0.0979543, `000000045_gompertz` = 0.135268, `000000046_gompertz` = 0.260895, `000000047_gompertz` = 0.507332, `000000049_gompertz` = 1.83762, `000000050_gompertz` = 0.183626, `000000051_gompertz` = 0.119591, `000000052_gompertz` = 0.166217, `000000053_gompertz` = 0.375883, `000000054_gompertz` = 0.159972, `000000055_gompertz` = 0.378644, `000000056_gompertz` = 0.198184, `000000057_gompertz` = 0.854106, `000000058_gompertz` = 0.113661, `000000059_gompertz` = 0.0460331, `000000060_gompertz` = 0.261158, `000000061_gompertz` = 0.349721, `000000062_gompertz` = 0.155654, `000000063_gompertz` = 0.257054, `000000065_gompertz` = 0.862269, `000000066_gompertz` = 0.252522, `000000067_gompertz` = 1.27307, `000000068_gompertz` = 0.306418, `000000069_gompertz` = 0.102574, diff --git a/tests/testthat/_snaps/hc-burrlioz/hc_boron.csv b/tests/testthat/_snaps/hc-burrlioz/hc_boron.csv index b2605b86e..abb980a11 100644 --- a/tests/testthat/_snaps/hc-burrlioz/hc_boron.csv +++ b/tests/testthat/_snaps/hc-burrlioz/hc_boron.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -invpareto,5,0.386944,0.347873,0.195882,1.10643,1,non-parametric,10,1,"c(`000000001_invpareto` = 0.982745, `000000002_invpareto` = 0.93683, `000000003_invpareto` = 0.178607, `000000004_invpareto` = 0.292255, `000000005_invpareto` = 0.410782, `000000006_invpareto` = 0.342529, `000000007_invpareto` = 0.255384, `000000008_invpareto` = 1.14234, `000000009_invpareto` = 0.339202, `000000010_invpareto` = 0.476697)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +invpareto,0.05,0.386944,0.347873,0.195882,1.10643,1,non-parametric,10,1,"c(`000000001_invpareto` = 0.982745, `000000002_invpareto` = 0.93683, `000000003_invpareto` = 0.178607, `000000004_invpareto` = 0.292255, `000000005_invpareto` = 0.410782, `000000006_invpareto` = 0.342529, `000000007_invpareto` = 0.255384, `000000008_invpareto` = 1.14234, `000000009_invpareto` = 0.339202, `000000010_invpareto` = 0.476697)" diff --git a/tests/testthat/_snaps/hc-burrlioz/hc_boron0.csv b/tests/testthat/_snaps/hc-burrlioz/hc_boron0.csv index 120b25d90..481b58f95 100644 --- a/tests/testthat/_snaps/hc-burrlioz/hc_boron0.csv +++ b/tests/testthat/_snaps/hc-burrlioz/hc_boron0.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -invpareto,5,0.386944,0.347873,0.195882,1.10643,1,non-parametric,10,1,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +invpareto,0.05,0.386944,0.347873,0.195882,1.10643,1,non-parametric,10,1,numeric(0) diff --git a/tests/testthat/_snaps/hc-burrlioz/hc_boron_no_ci.csv b/tests/testthat/_snaps/hc-burrlioz/hc_boron_no_ci.csv index bead4cd06..7c53f3f8f 100644 --- a/tests/testthat/_snaps/hc-burrlioz/hc_boron_no_ci.csv +++ b/tests/testthat/_snaps/hc-burrlioz/hc_boron_no_ci.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -invpareto,5,0.386944,NA,NA,NA,1,non-parametric,0,NA,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +invpareto,0.05,0.386944,NA,NA,NA,1,non-parametric,0,NA,numeric(0) diff --git a/tests/testthat/_snaps/hc-burrlioz/hc_burrIII3.csv b/tests/testthat/_snaps/hc-burrlioz/hc_burrIII3.csv index 4fd503c54..5f1617159 100644 --- a/tests/testthat/_snaps/hc-burrlioz/hc_burrIII3.csv +++ b/tests/testthat/_snaps/hc-burrlioz/hc_burrIII3.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -burrIII3,5,0.0180122,0.0330222,0.00257335,0.0960996,1,non-parametric,10,1,"c(`000000001_burrIII3` = 0.00216345, `000000002_burrIII3` = 0.0135629, `000000003_burrIII3` = 0.0249016, `000000004_burrIII3` = 0.00398519, `000000005_burrIII3` = 0.00525064, `000000006_burrIII3` = 0.0456991, `000000007_burrIII3` = 0.0174388, `000000008_burrIII3` = 0.0371055, `000000009_burrIII3` = 0.00563071, `000000010_burrIII3` = 0.110732)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +burrIII3,0.05,0.0180122,0.0330222,0.00257335,0.0960996,1,non-parametric,10,1,"c(`000000001_burrIII3` = 0.00216345, `000000002_burrIII3` = 0.0135629, `000000003_burrIII3` = 0.0249016, `000000004_burrIII3` = 0.00398519, `000000005_burrIII3` = 0.00525064, `000000006_burrIII3` = 0.0456991, `000000007_burrIII3` = 0.0174388, `000000008_burrIII3` = 0.0371055, `000000009_burrIII3` = 0.00563071, `000000010_burrIII3` = 0.110732)" diff --git a/tests/testthat/_snaps/hc-burrlioz/hc_burrIII3_parametric.csv b/tests/testthat/_snaps/hc-burrlioz/hc_burrIII3_parametric.csv index 544baedab..d0e0ea801 100644 --- a/tests/testthat/_snaps/hc-burrlioz/hc_burrIII3_parametric.csv +++ b/tests/testthat/_snaps/hc-burrlioz/hc_burrIII3_parametric.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -burrIII3,5,0.0180122,0.0149874,0.00621681,0.0503455,1,parametric,10,1,"c(`000000001_burrIII3` = 0.024927, `000000002_burrIII3` = 0.0532566, `000000003_burrIII3` = 0.0161967, `000000004_burrIII3` = 0.0403185, `000000005_burrIII3` = 0.0122971, `000000006_burrIII3` = 0.0185225, `000000007_burrIII3` = 0.0113264, `000000008_burrIII3` = 0.00490145, `000000009_burrIII3` = 0.0107475, `000000010_burrIII3` = 0.0155147)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +burrIII3,0.05,0.0180122,0.0149874,0.00621681,0.0503455,1,parametric,10,1,"c(`000000001_burrIII3` = 0.024927, `000000002_burrIII3` = 0.0532566, `000000003_burrIII3` = 0.0161967, `000000004_burrIII3` = 0.0403185, `000000005_burrIII3` = 0.0122971, `000000006_burrIII3` = 0.0185225, `000000007_burrIII3` = 0.0113264, `000000008_burrIII3` = 0.00490145, `000000009_burrIII3` = 0.0107475, `000000010_burrIII3` = 0.0155147)" diff --git a/tests/testthat/_snaps/hc-root.md b/tests/testthat/_snaps/hc-root.md index 182a0a84b..287c1a375 100644 --- a/tests/testthat/_snaps/hc-root.md +++ b/tests/testthat/_snaps/hc-root.md @@ -4,9 +4,9 @@ hc_multi Output # A tibble: 1 x 11 - dist percent est se lcl ucl wt method nboot pboot samples - > - 1 average 5 1.68 NA NA NA 1 parametric 0 NA + dist proportion est se lcl ucl wt method nboot pboot samples + + 1 average 0.05 1.68 NA NA NA 1 parametr~ 0 NA # hc multi_ci all @@ -14,9 +14,9 @@ hc_multi Output # A tibble: 1 x 11 - dist percent est se lcl ucl wt method nboot pboot samples - > - 1 average 5 1.26 NA NA NA 1 parametric 0 NA + dist proportion est se lcl ucl wt method nboot pboot samples + + 1 average 0.05 1.26 NA NA NA 1 parametr~ 0 NA # hc multi_ci all multiple hcs @@ -24,10 +24,10 @@ hc_multi Output # A tibble: 2 x 11 - dist percent est se lcl ucl wt method nboot pboot samples - > - 1 average 5 1.26 NA NA NA 1 parametric 0 NA - 2 average 10 2.38 NA NA NA 1 parametric 0 NA + dist proportion est se lcl ucl wt method nboot pboot samples + + 1 average 0.05 1.26 NA NA NA 1 parametr~ 0 NA + 2 average 0.1 2.38 NA NA NA 1 parametr~ 0 NA # hc multi_ci all multiple hcs cis @@ -35,10 +35,10 @@ hc_multi Output # A tibble: 2 x 11 - dist percent est se lcl ucl wt method nboot pboot samples - > - 1 average 5 1.26 0.621 0.492 2.12 1 parametric 10 1 - 2 average 10 2.38 0.930 1.17 3.60 1 parametric 10 1 + dist proportion est se lcl ucl wt method nboot pboot samples + + 1 average 0.05 1.26 0.621 0.492 2.12 1 parametr~ 10 1 + 2 average 0.1 2.38 0.930 1.17 3.60 1 parametr~ 10 1 # hc multi_ci lnorm ci @@ -46,9 +46,9 @@ hc_average Output # A tibble: 1 x 11 - dist percent est se lcl ucl wt method nboot pboot samples - > - 1 average 5 1.68 0.529 0.948 2.76 1 parametric 100 1 + dist proportion est se lcl ucl wt method nboot pboot samples + + 1 average 0.05 1.68 0.529 0.948 2.76 1 parametr~ 100 1 --- @@ -56,7 +56,7 @@ hc_multi Output # A tibble: 1 x 11 - dist percent est se lcl ucl wt method nboot pboot samples - > - 1 average 5 1.68 0.535 0.979 2.99 1 parametric 100 1 + dist proportion est se lcl ucl wt method nboot pboot samples + + 1 average 0.05 1.68 0.535 0.979 2.99 1 parametr~ 100 1 diff --git a/tests/testthat/_snaps/hc/hc.csv b/tests/testthat/_snaps/hc/hc.csv index 7cf7ca328..fef98f208 100644 --- a/tests/testthat/_snaps/hc/hc.csv +++ b/tests/testthat/_snaps/hc/hc.csv @@ -1,7 +1,7 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -gamma,5,1.07428,0.983875,0.709111,3.19472,0.356574,parametric,10,1,"c(`000000001_gamma` = 0.987785, `000000002_gamma` = 3.15112, `000000003_gamma` = 0.84656, `000000004_gamma` = 0.70604, `000000005_gamma` = 1.98672, `000000006_gamma` = 0.873452, `000000007_gamma` = 1.18798, `000000008_gamma` = 0.836688, `000000009_gamma` = 0.719689, `000000010_gamma` = 3.20738)" -lgumbel,5,1.76939,0.401763,1.39032,2.63032,0.0134466,parametric,10,1,"c(`000000001_lgumbel` = 2.2833, `000000002_lgumbel` = 1.48094, `000000003_lgumbel` = 2.12922, `000000004_lgumbel` = 2.36856, `000000005_lgumbel` = 1.81154, `000000006_lgumbel` = 1.96535, `000000007_lgumbel` = 1.36401, `000000008_lgumbel` = 1.93797, `000000009_lgumbel` = 2.70632, `000000010_lgumbel` = 2.09232)" -llogis,5,1.56226,0.834776,0.851639,3.37274,0.0656452,parametric,10,1,"c(`000000001_llogis` = 0.751505, `000000002_llogis` = 3.04268, `000000003_llogis` = 2.10953, `000000004_llogis` = 2.22634, `000000005_llogis` = 1.30249, `000000006_llogis` = 2.52802, `000000007_llogis` = 3.46857, `000000008_llogis` = 2.04533, `000000009_llogis` = 1.85618, `000000010_llogis` = 1.19654)" -lnorm,5,1.68117,0.823601,0.8894,3.02109,0.177236,parametric,10,1,"c(`000000001_lnorm` = 3.09183, `000000002_lnorm` = 2.42899, `000000003_lnorm` = 1.325, `000000004_lnorm` = 1.61081, `000000005_lnorm` = 2.60329, `000000006_lnorm` = 0.865973, `000000007_lnorm` = 2.77742, `000000008_lnorm` = 1.19715, `000000009_lnorm` = 2.45546, `000000010_lnorm` = 0.970094)" -lnorm_lnorm,5,1.54141,0.329119,0.952154,1.82195,0.0296268,parametric,10,1,"c(`000000001_lnorm_lnorm` = 1.64166, `000000002_lnorm_lnorm` = 1.67909, `000000003_lnorm_lnorm` = 1.80876, `000000004_lnorm_lnorm` = 0.921821, `000000005_lnorm_lnorm` = 1.68365, `000000006_lnorm_lnorm` = 1.28523, `000000007_lnorm_lnorm` = 1.82578, `000000008_lnorm_lnorm` = 1.05663, `000000009_lnorm_lnorm` = 1.20995, `000000010_lnorm_lnorm` = 1.67578)" -weibull,5,1.08673,0.895134,0.819219,3.40858,0.357472,parametric,10,1,"c(`000000001_weibull` = 1.67077, `000000002_weibull` = 0.93999, `000000003_weibull` = 1.45323, `000000004_weibull` = 3.60435, `000000005_weibull` = 1.0464, `000000006_weibull` = 1.48364, `000000007_weibull` = 2.08463, `000000008_weibull` = 1.05416, `000000009_weibull` = 2.73428, `000000010_weibull` = 0.784157)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +gamma,0.05,1.07428,0.983875,0.709111,3.19472,0.356574,parametric,10,1,"c(`000000001_gamma` = 0.987785, `000000002_gamma` = 3.15112, `000000003_gamma` = 0.84656, `000000004_gamma` = 0.70604, `000000005_gamma` = 1.98672, `000000006_gamma` = 0.873452, `000000007_gamma` = 1.18798, `000000008_gamma` = 0.836688, `000000009_gamma` = 0.719689, `000000010_gamma` = 3.20738)" +lgumbel,0.05,1.76939,0.401763,1.39032,2.63032,0.0134466,parametric,10,1,"c(`000000001_lgumbel` = 2.2833, `000000002_lgumbel` = 1.48094, `000000003_lgumbel` = 2.12922, `000000004_lgumbel` = 2.36856, `000000005_lgumbel` = 1.81154, `000000006_lgumbel` = 1.96535, `000000007_lgumbel` = 1.36401, `000000008_lgumbel` = 1.93797, `000000009_lgumbel` = 2.70632, `000000010_lgumbel` = 2.09232)" +llogis,0.05,1.56226,0.834776,0.851639,3.37274,0.0656452,parametric,10,1,"c(`000000001_llogis` = 0.751505, `000000002_llogis` = 3.04268, `000000003_llogis` = 2.10953, `000000004_llogis` = 2.22634, `000000005_llogis` = 1.30249, `000000006_llogis` = 2.52802, `000000007_llogis` = 3.46857, `000000008_llogis` = 2.04533, `000000009_llogis` = 1.85618, `000000010_llogis` = 1.19654)" 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`000000005_weibull` = 1.0464, `000000006_weibull` = 1.48364, `000000007_weibull` = 2.08463, `000000008_weibull` = 1.05416, `000000009_weibull` = 2.73428, `000000010_weibull` = 0.784157)" diff --git a/tests/testthat/_snaps/hc/hc114.csv b/tests/testthat/_snaps/hc/hc114.csv index f3d49f7dc..2c8ac5871 100644 --- a/tests/testthat/_snaps/hc/hc114.csv +++ b/tests/testthat/_snaps/hc/hc114.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples average,NA,NA,NA,NA,NA,1,parametric,0,NA,numeric(0) diff --git a/tests/testthat/_snaps/hc/hc122.csv b/tests/testthat/_snaps/hc/hc122.csv index a249ffecf..4662ab640 100644 --- a/tests/testthat/_snaps/hc/hc122.csv +++ b/tests/testthat/_snaps/hc/hc122.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples average,0,0,NA,NA,NA,1,parametric,0,NA,numeric(0) diff --git a/tests/testthat/_snaps/hc/hc130.csv b/tests/testthat/_snaps/hc/hc130.csv index e26595e4b..14255a320 100644 --- a/tests/testthat/_snaps/hc/hc130.csv +++ b/tests/testthat/_snaps/hc/hc130.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,100,Inf,NA,NA,NA,1,parametric,0,NA,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,1,Inf,NA,NA,NA,1,parametric,0,NA,numeric(0) diff --git a/tests/testthat/_snaps/hc/hc138.csv b/tests/testthat/_snaps/hc/hc138.csv index 94dff1a1b..4c9e152b2 100644 --- a/tests/testthat/_snaps/hc/hc138.csv +++ b/tests/testthat/_snaps/hc/hc138.csv @@ -1,3 +1,3 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,1,0.721365,NA,NA,NA,1,parametric,0,NA,numeric(0) -average,99,232.735,NA,NA,NA,1,parametric,0,NA,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.01,0.721365,NA,NA,NA,1,parametric,0,NA,numeric(0) +average,0.99,232.735,NA,NA,NA,1,parametric,0,NA,numeric(0) diff --git a/tests/testthat/_snaps/hc/hc145.csv b/tests/testthat/_snaps/hc/hc145.csv index 989565da9..77400d9c6 100644 --- a/tests/testthat/_snaps/hc/hc145.csv +++ b/tests/testthat/_snaps/hc/hc145.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.24152,NA,NA,NA,1,parametric,0,NA,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.24152,NA,NA,NA,1,parametric,0,NA,numeric(0) diff --git a/tests/testthat/_snaps/hc/hc153.csv b/tests/testthat/_snaps/hc/hc153.csv index 69ad55478..285c33882 100644 --- a/tests/testthat/_snaps/hc/hc153.csv +++ b/tests/testthat/_snaps/hc/hc153.csv @@ -1,100 +1,100 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,1,0.721365,NA,NA,NA,1,parametric,0,NA,numeric(0) -average,2,1.0119,NA,NA,NA,1,parametric,0,NA,numeric(0) -average,3,1.25428,NA,NA,NA,1,parametric,0,NA,numeric(0) 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+lnorm,0.86,49.5462,NA,NA,NA,1,parametric,0,NA,numeric(0) +lnorm,0.87,52.4628,NA,NA,NA,1,parametric,0,NA,numeric(0) +lnorm,0.88,55.7255,NA,NA,NA,1,parametric,0,NA,numeric(0) +lnorm,0.89,59.408,NA,NA,NA,1,parametric,0,NA,numeric(0) +lnorm,0.9,63.6082,NA,NA,NA,1,parametric,0,NA,numeric(0) +lnorm,0.91,68.4598,NA,NA,NA,1,parametric,0,NA,numeric(0) +lnorm,0.92,74.1506,NA,NA,NA,1,parametric,0,NA,numeric(0) +lnorm,0.93,80.9555,NA,NA,NA,1,parametric,0,NA,numeric(0) +lnorm,0.94,89.2962,NA,NA,NA,1,parametric,0,NA,numeric(0) +lnorm,0.95,99.8628,NA,NA,NA,1,parametric,0,NA,numeric(0) +lnorm,0.96,113.885,NA,NA,NA,1,parametric,0,NA,numeric(0) +lnorm,0.97,133.851,NA,NA,NA,1,parametric,0,NA,numeric(0) +lnorm,0.98,165.912,NA,NA,NA,1,parametric,0,NA,numeric(0) +lnorm,0.99,232.735,NA,NA,NA,1,parametric,0,NA,numeric(0) diff --git a/tests/testthat/_snaps/hc/hc168.csv b/tests/testthat/_snaps/hc/hc168.csv index 7b1066627..c2ae2c338 100644 --- a/tests/testthat/_snaps/hc/hc168.csv +++ b/tests/testthat/_snaps/hc/hc168.csv @@ -1,7 +1,7 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -gamma,5,1.07428,NA,NA,NA,0.356574,parametric,0,NA,numeric(0) -lgumbel,5,1.76939,NA,NA,NA,0.0134466,parametric,0,NA,numeric(0) -llogis,5,1.56226,NA,NA,NA,0.0656452,parametric,0,NA,numeric(0) -lnorm,5,1.68117,NA,NA,NA,0.177236,parametric,0,NA,numeric(0) -lnorm_lnorm,5,1.54141,NA,NA,NA,0.0296268,parametric,0,NA,numeric(0) -weibull,5,1.08673,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +gamma,0.05,1.07428,NA,NA,NA,0.356574,parametric,0,NA,numeric(0) +lgumbel,0.05,1.76939,NA,NA,NA,0.0134466,parametric,0,NA,numeric(0) +llogis,0.05,1.56226,NA,NA,NA,0.0656452,parametric,0,NA,numeric(0) +lnorm,0.05,1.68117,NA,NA,NA,0.177236,parametric,0,NA,numeric(0) +lnorm_lnorm,0.05,1.54141,NA,NA,NA,0.0296268,parametric,0,NA,numeric(0) +weibull,0.05,1.08673,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) diff --git a/tests/testthat/_snaps/hc/hc505.csv b/tests/testthat/_snaps/hc/hc505.csv index 6d808ba23..c94f21a4d 100644 --- a/tests/testthat/_snaps/hc/hc505.csv +++ b/tests/testthat/_snaps/hc/hc505.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,50.5,13.1603,NA,NA,NA,1,parametric,0,NA,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.505,13.1603,NA,NA,NA,1,parametric,0,NA,numeric(0) diff --git a/tests/testthat/_snaps/hc/hc_1.csv b/tests/testthat/_snaps/hc/hc_1.csv index e1ddd15a1..bce0886b9 100644 --- a/tests/testthat/_snaps/hc/hc_1.csv +++ b/tests/testthat/_snaps/hc/hc_1.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68117,NA,0.934605,0.934605,1,parametric,1,1,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68117,NA,0.934605,0.934605,1,parametric,1,1,numeric(0) diff --git a/tests/testthat/_snaps/hc/hc_30.csv b/tests/testthat/_snaps/hc/hc_30.csv index 4bbd6dc0b..85812ea95 100644 --- a/tests/testthat/_snaps/hc/hc_30.csv +++ b/tests/testthat/_snaps/hc/hc_30.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,0.9294,0.0164012,0.886164,0.940088,1,parametric,100,0.93,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,0.9294,0.0164012,0.886164,0.940088,1,parametric,100,0.93,numeric(0) diff --git a/tests/testthat/_snaps/hc/hc_boron.csv b/tests/testthat/_snaps/hc/hc_boron.csv index b2605b86e..abb980a11 100644 --- a/tests/testthat/_snaps/hc/hc_boron.csv +++ b/tests/testthat/_snaps/hc/hc_boron.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -invpareto,5,0.386944,0.347873,0.195882,1.10643,1,non-parametric,10,1,"c(`000000001_invpareto` = 0.982745, `000000002_invpareto` = 0.93683, `000000003_invpareto` = 0.178607, `000000004_invpareto` = 0.292255, `000000005_invpareto` = 0.410782, `000000006_invpareto` = 0.342529, `000000007_invpareto` = 0.255384, `000000008_invpareto` = 1.14234, `000000009_invpareto` = 0.339202, `000000010_invpareto` = 0.476697)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +invpareto,0.05,0.386944,0.347873,0.195882,1.10643,1,non-parametric,10,1,"c(`000000001_invpareto` = 0.982745, `000000002_invpareto` = 0.93683, `000000003_invpareto` = 0.178607, `000000004_invpareto` = 0.292255, `000000005_invpareto` = 0.410782, `000000006_invpareto` = 0.342529, `000000007_invpareto` = 0.255384, `000000008_invpareto` = 1.14234, `000000009_invpareto` = 0.339202, `000000010_invpareto` = 0.476697)" diff --git a/tests/testthat/_snaps/hc/hc_burrIII3.csv b/tests/testthat/_snaps/hc/hc_burrIII3.csv index 4fd503c54..5f1617159 100644 --- a/tests/testthat/_snaps/hc/hc_burrIII3.csv +++ b/tests/testthat/_snaps/hc/hc_burrIII3.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -burrIII3,5,0.0180122,0.0330222,0.00257335,0.0960996,1,non-parametric,10,1,"c(`000000001_burrIII3` = 0.00216345, `000000002_burrIII3` = 0.0135629, `000000003_burrIII3` = 0.0249016, `000000004_burrIII3` = 0.00398519, `000000005_burrIII3` = 0.00525064, `000000006_burrIII3` = 0.0456991, `000000007_burrIII3` = 0.0174388, `000000008_burrIII3` = 0.0371055, `000000009_burrIII3` = 0.00563071, `000000010_burrIII3` = 0.110732)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +burrIII3,0.05,0.0180122,0.0330222,0.00257335,0.0960996,1,non-parametric,10,1,"c(`000000001_burrIII3` = 0.00216345, `000000002_burrIII3` = 0.0135629, `000000003_burrIII3` = 0.0249016, `000000004_burrIII3` = 0.00398519, `000000005_burrIII3` = 0.00525064, `000000006_burrIII3` = 0.0456991, `000000007_burrIII3` = 0.0174388, `000000008_burrIII3` = 0.0371055, `000000009_burrIII3` = 0.00563071, `000000010_burrIII3` = 0.110732)" diff --git a/tests/testthat/_snaps/hc/hc_burrIII3_parametric.csv b/tests/testthat/_snaps/hc/hc_burrIII3_parametric.csv index 544baedab..d0e0ea801 100644 --- a/tests/testthat/_snaps/hc/hc_burrIII3_parametric.csv +++ b/tests/testthat/_snaps/hc/hc_burrIII3_parametric.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -burrIII3,5,0.0180122,0.0149874,0.00621681,0.0503455,1,parametric,10,1,"c(`000000001_burrIII3` = 0.024927, `000000002_burrIII3` = 0.0532566, `000000003_burrIII3` = 0.0161967, `000000004_burrIII3` = 0.0403185, `000000005_burrIII3` = 0.0122971, `000000006_burrIII3` = 0.0185225, `000000007_burrIII3` = 0.0113264, `000000008_burrIII3` = 0.00490145, `000000009_burrIII3` = 0.0107475, `000000010_burrIII3` = 0.0155147)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +burrIII3,0.05,0.0180122,0.0149874,0.00621681,0.0503455,1,parametric,10,1,"c(`000000001_burrIII3` = 0.024927, `000000002_burrIII3` = 0.0532566, `000000003_burrIII3` = 0.0161967, `000000004_burrIII3` = 0.0403185, `000000005_burrIII3` = 0.0122971, `000000006_burrIII3` = 0.0185225, `000000007_burrIII3` = 0.0113264, `000000008_burrIII3` = 0.00490145, `000000009_burrIII3` = 0.0107475, `000000010_burrIII3` = 0.0155147)" diff --git a/tests/testthat/_snaps/hc/hc_cis.csv b/tests/testthat/_snaps/hc/hc_cis.csv index cfb9a6998..9c9a50850 100644 --- a/tests/testthat/_snaps/hc/hc_cis.csv +++ b/tests/testthat/_snaps/hc/hc_cis.csv @@ -1,5 +1,5 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68117,0.682856,0.916051,3.47923,1,parametric,1000,1,"c(`000000001_lnorm` = 1.29091, `000000002_lnorm` = 2.32183, `000000003_lnorm` = 1.62344, `000000004_lnorm` = 1.434, `000000005_lnorm` = 1.81625, `000000006_lnorm` = 2.64477, `000000007_lnorm` = 1.9797, `000000008_lnorm` = 1.40648, `000000009_lnorm` = 1.75897, `000000010_lnorm` = 2.52819, `000000011_lnorm` = 1.75286, `000000012_lnorm` = 2.64467, `000000013_lnorm` = 1.89607, `000000014_lnorm` = 1.42891, `000000015_lnorm` = 2.04596, `000000016_lnorm` = 1.076, `000000017_lnorm` = 1.82926, `000000018_lnorm` = 1.77754, +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68117,0.682856,0.916051,3.47923,1,parametric,1000,1,"c(`000000001_lnorm` = 1.29091, `000000002_lnorm` = 2.32183, `000000003_lnorm` = 1.62344, `000000004_lnorm` = 1.434, `000000005_lnorm` = 1.81625, `000000006_lnorm` = 2.64477, `000000007_lnorm` = 1.9797, `000000008_lnorm` = 1.40648, `000000009_lnorm` = 1.75897, `000000010_lnorm` = 2.52819, `000000011_lnorm` = 1.75286, `000000012_lnorm` = 2.64467, `000000013_lnorm` = 1.89607, `000000014_lnorm` = 1.42891, `000000015_lnorm` = 2.04596, `000000016_lnorm` = 1.076, `000000017_lnorm` = 1.82926, `000000018_lnorm` = 1.77754, `000000019_lnorm` = 1.81362, `000000020_lnorm` = 1.56522, `000000021_lnorm` = 1.31328, `000000022_lnorm` = 2.34267, `000000023_lnorm` = 1.95807, `000000024_lnorm` = 0.979764, `000000025_lnorm` = 1.90104, `000000026_lnorm` = 1.31927, `000000027_lnorm` = 1.22681, `000000028_lnorm` = 1.36297, `000000029_lnorm` = 2.03217, `000000030_lnorm` = 1.48939, `000000031_lnorm` = 2.32383, `000000032_lnorm` = 2.76469, `000000033_lnorm` = 2.12493, `000000034_lnorm` = 1.16584, `000000035_lnorm` = 2.24326, `000000036_lnorm` = 1.85553, `000000037_lnorm` = 2.58016, `000000038_lnorm` = 2.13527, `000000039_lnorm` = 1.12606, `000000040_lnorm` = 1.92818, `000000041_lnorm` = 2.02068, `000000042_lnorm` = 1.98607, `000000043_lnorm` = 2.96207, `000000044_lnorm` = 1.00953, `000000045_lnorm` = 0.524816, `000000046_lnorm` = 2.7306, `000000047_lnorm` = 1.49195, `000000048_lnorm` = 1.52999, `000000049_lnorm` = 1.91416, `000000050_lnorm` = 0.919343, `000000051_lnorm` = 0.984984, `000000052_lnorm` = 1.63899, `000000053_lnorm` = 1.26687, `000000054_lnorm` = 1.31936, `000000055_lnorm` = 1.15461, `000000056_lnorm` = 1.35223, `000000057_lnorm` = 2.41231, `000000058_lnorm` = 0.732408, `000000059_lnorm` = 1.9412, `000000060_lnorm` = 1.82985, `000000061_lnorm` = 1.80799, `000000062_lnorm` = 1.09987, `000000063_lnorm` = 1.46472, `000000064_lnorm` = 1.07241, `000000065_lnorm` = 1.27812, `000000066_lnorm` = 1.83395, `000000067_lnorm` = 1.30446, `000000068_lnorm` = 1.2981, `000000069_lnorm` = 1.20418, `000000070_lnorm` = 2.83823, `000000071_lnorm` = 1.18793, `000000072_lnorm` = 2.01091, diff --git a/tests/testthat/_snaps/hc/hc_cis_chloride50.csv b/tests/testthat/_snaps/hc/hc_cis_chloride50.csv index 59adb8346..bf0d8a46d 100644 --- a/tests/testthat/_snaps/hc/hc_cis_chloride50.csv +++ b/tests/testthat/_snaps/hc/hc_cis_chloride50.csv @@ -1,3 +1,3 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,samples -lnorm_lnorm,5,36.8763,NA,NA,NA,0.617286,parametric,1000,numeric(0) -llogis_llogis,5,36.9096,NA,NA,NA,0.382714,parametric,1000,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,samples +lnorm_lnorm,0.05,36.8763,NA,NA,NA,0.617286,parametric,1000,numeric(0) +llogis_llogis,0.05,36.9096,NA,NA,NA,0.382714,parametric,1000,numeric(0) diff --git a/tests/testthat/_snaps/hc/hc_cis_level08.csv b/tests/testthat/_snaps/hc/hc_cis_level08.csv index 18a61a167..3d8c909a9 100644 --- a/tests/testthat/_snaps/hc/hc_cis_level08.csv +++ b/tests/testthat/_snaps/hc/hc_cis_level08.csv @@ -1,5 +1,5 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68117,0.682856,1.11342,2.76012,1,parametric,1000,1,"c(`000000001_lnorm` = 1.29091, `000000002_lnorm` = 2.32183, `000000003_lnorm` = 1.62344, `000000004_lnorm` = 1.434, `000000005_lnorm` = 1.81625, `000000006_lnorm` = 2.64477, `000000007_lnorm` = 1.9797, `000000008_lnorm` = 1.40648, `000000009_lnorm` = 1.75897, `000000010_lnorm` = 2.52819, `000000011_lnorm` = 1.75286, `000000012_lnorm` = 2.64467, `000000013_lnorm` = 1.89607, `000000014_lnorm` = 1.42891, `000000015_lnorm` = 2.04596, `000000016_lnorm` = 1.076, `000000017_lnorm` = 1.82926, `000000018_lnorm` = 1.77754, +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68117,0.682856,1.11342,2.76012,1,parametric,1000,1,"c(`000000001_lnorm` = 1.29091, `000000002_lnorm` = 2.32183, `000000003_lnorm` = 1.62344, `000000004_lnorm` = 1.434, `000000005_lnorm` = 1.81625, `000000006_lnorm` = 2.64477, `000000007_lnorm` = 1.9797, `000000008_lnorm` = 1.40648, `000000009_lnorm` = 1.75897, `000000010_lnorm` = 2.52819, `000000011_lnorm` = 1.75286, `000000012_lnorm` = 2.64467, `000000013_lnorm` = 1.89607, `000000014_lnorm` = 1.42891, `000000015_lnorm` = 2.04596, `000000016_lnorm` = 1.076, `000000017_lnorm` = 1.82926, `000000018_lnorm` = 1.77754, `000000019_lnorm` = 1.81362, `000000020_lnorm` = 1.56522, `000000021_lnorm` = 1.31328, `000000022_lnorm` = 2.34267, `000000023_lnorm` = 1.95807, `000000024_lnorm` = 0.979764, `000000025_lnorm` = 1.90104, `000000026_lnorm` = 1.31927, `000000027_lnorm` = 1.22681, `000000028_lnorm` = 1.36297, `000000029_lnorm` = 2.03217, `000000030_lnorm` = 1.48939, `000000031_lnorm` = 2.32383, `000000032_lnorm` = 2.76469, `000000033_lnorm` = 2.12493, `000000034_lnorm` = 1.16584, `000000035_lnorm` = 2.24326, `000000036_lnorm` = 1.85553, `000000037_lnorm` = 2.58016, `000000038_lnorm` = 2.13527, `000000039_lnorm` = 1.12606, `000000040_lnorm` = 1.92818, `000000041_lnorm` = 2.02068, `000000042_lnorm` = 1.98607, `000000043_lnorm` = 2.96207, `000000044_lnorm` = 1.00953, `000000045_lnorm` = 0.524816, `000000046_lnorm` = 2.7306, `000000047_lnorm` = 1.49195, `000000048_lnorm` = 1.52999, `000000049_lnorm` = 1.91416, `000000050_lnorm` = 0.919343, `000000051_lnorm` = 0.984984, `000000052_lnorm` = 1.63899, `000000053_lnorm` = 1.26687, `000000054_lnorm` = 1.31936, `000000055_lnorm` = 1.15461, `000000056_lnorm` = 1.35223, `000000057_lnorm` = 2.41231, `000000058_lnorm` = 0.732408, `000000059_lnorm` = 1.9412, `000000060_lnorm` = 1.82985, `000000061_lnorm` = 1.80799, `000000062_lnorm` = 1.09987, `000000063_lnorm` = 1.46472, `000000064_lnorm` = 1.07241, `000000065_lnorm` = 1.27812, `000000066_lnorm` = 1.83395, `000000067_lnorm` = 1.30446, `000000068_lnorm` = 1.2981, `000000069_lnorm` = 1.20418, `000000070_lnorm` = 2.83823, `000000071_lnorm` = 1.18793, `000000072_lnorm` = 2.01091, diff --git a/tests/testthat/_snaps/hc/hc_err_avg.csv b/tests/testthat/_snaps/hc/hc_err_avg.csv index 2a79957c3..f5df7bb92 100644 --- a/tests/testthat/_snaps/hc/hc_err_avg.csv +++ b/tests/testthat/_snaps/hc/hc_err_avg.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,samples -average,5,0.945788,NA,NA,NA,1,parametric,100,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,samples +average,0.05,0.945788,NA,NA,NA,1,parametric,100,numeric(0) diff --git a/tests/testthat/_snaps/hc/hc_err_two.csv b/tests/testthat/_snaps/hc/hc_err_two.csv index 72c28c093..e7d6ea8b2 100644 --- a/tests/testthat/_snaps/hc/hc_err_two.csv +++ b/tests/testthat/_snaps/hc/hc_err_two.csv @@ -1,3 +1,3 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,samples -lnorm,5,1.29028,0.140037,1.08208,1.59418,2.15098e-11,parametric,100,numeric(0) -llogis_llogis,5,0.945788,NA,NA,NA,1,parametric,100,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,samples +lnorm,0.05,1.29028,0.140037,1.08208,1.59418,2.15098e-11,parametric,100,numeric(0) +llogis_llogis,0.05,0.945788,NA,NA,NA,1,parametric,100,numeric(0) diff --git a/tests/testthat/_snaps/hc/hc_fix.csv b/tests/testthat/_snaps/hc/hc_fix.csv index f4c9cb8ab..c767c2a5a 100644 --- a/tests/testthat/_snaps/hc/hc_fix.csv +++ b/tests/testthat/_snaps/hc/hc_fix.csv @@ -1,5 +1,5 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68947,0.528953,0.921854,2.95419,1,parametric,100,1,"c(`000000001_multi` = 1.10357, `000000002_multi` = 1.5793, `000000003_multi` = 2.08052, `000000004_multi` = 2.53789, `000000005_multi` = 2.12301, `000000006_multi` = 0.594466, `000000007_multi` = 2.36326, `000000008_multi` = 1.52539, `000000009_multi` = 1.4663, `000000010_multi` = 2.90171, `000000011_multi` = 1.25871, `000000012_multi` = 1.24921, `000000013_multi` = 1.15486, `000000014_multi` = 2.20717, `000000015_multi` = 2.0311, `000000016_multi` = 2.02475, `000000017_multi` = 1.47116, `000000018_multi` = 1.20611, +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68947,0.528953,0.921854,2.95419,1,parametric,100,1,"c(`000000001_multi` = 1.10357, `000000002_multi` = 1.5793, `000000003_multi` = 2.08052, `000000004_multi` = 2.53789, `000000005_multi` = 2.12301, `000000006_multi` = 0.594466, `000000007_multi` = 2.36326, `000000008_multi` = 1.52539, `000000009_multi` = 1.4663, `000000010_multi` = 2.90171, `000000011_multi` = 1.25871, `000000012_multi` = 1.24921, `000000013_multi` = 1.15486, `000000014_multi` = 2.20717, `000000015_multi` = 2.0311, `000000016_multi` = 2.02475, `000000017_multi` = 1.47116, `000000018_multi` = 1.20611, `000000019_multi` = 1.64372, `000000020_multi` = 1.12373, `000000021_multi` = 1.44884, `000000022_multi` = 1.88825, `000000023_multi` = 1.35736, `000000024_multi` = 1.18551, `000000025_multi` = 3.19107, `000000026_multi` = 2.1446, `000000027_multi` = 1.9026, `000000028_multi` = 1.58645, `000000029_multi` = 1.54455, `000000030_multi` = 1.50489, `000000031_multi` = 1.16407, `000000032_multi` = 1.78667, `000000033_multi` = 1.1176, `000000034_multi` = 1.80585, `000000035_multi` = 1.95938, `000000036_multi` = 1.1355, `000000037_multi` = 1.54795, `000000038_multi` = 1.6452, `000000039_multi` = 1.43524, `000000040_multi` = 2.46175, `000000041_multi` = 1.35685, `000000042_multi` = 3.28089, `000000043_multi` = 2.65472, `000000044_multi` = 1.09977, `000000045_multi` = 0.643482, `000000046_multi` = 2.17547, `000000047_multi` = 1.51608, `000000048_multi` = 2.14445, `000000049_multi` = 2.25366, `000000050_multi` = 1.65013, `000000051_multi` = 1.39619, `000000052_multi` = 0.997734, `000000053_multi` = 1.4514, `000000054_multi` = 2.00727, `000000055_multi` = 1.41036, `000000056_multi` = 1.01034, `000000057_multi` = 1.55153, `000000058_multi` = 1.73587, `000000059_multi` = 1.65546, `000000060_multi` = 1.9081, `000000061_multi` = 1.24247, `000000062_multi` = 1.0203, `000000063_multi` = 0.916669, `000000064_multi` = 1.88521, `000000065_multi` = 1.24127, `000000066_multi` = 1.93069, `000000067_multi` = 1.6957, `000000068_multi` = 1.34166, `000000069_multi` = 0.927584, `000000070_multi` = 1.76922, `000000071_multi` = 1.82751, `000000072_multi` = 1.71645, diff --git a/tests/testthat/_snaps/hc/hc_fixmulti.csv b/tests/testthat/_snaps/hc/hc_fixmulti.csv index fcef15f67..b3ac15f32 100644 --- a/tests/testthat/_snaps/hc/hc_fixmulti.csv +++ b/tests/testthat/_snaps/hc/hc_fixmulti.csv @@ -1,11 +1,11 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68947,0.528953,0.921854,2.95419,1,parametric,100,1,"c(`000000001_multi` = 1.10357, `000000002_multi` = 1.5793, `000000003_multi` = 2.08052, `000000004_multi` = 2.53789, `000000005_multi` = 2.12301, `000000006_multi` = 0.594466, `000000007_multi` = 2.36326, `000000008_multi` = 1.52539, `000000009_multi` = 1.4663, `000000010_multi` = 2.90171, `000000011_multi` = 1.25871, `000000012_multi` = 1.24921, `000000013_multi` = 1.15486, `000000014_multi` = 2.20717, `000000015_multi` = 2.0311, `000000016_multi` = 2.02475, `000000017_multi` = 1.47116, `000000018_multi` = 1.20611, +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68947,0.528953,0.921854,2.95419,1,parametric,100,1,"c(`000000001_multi` = 1.10357, `000000002_multi` = 1.5793, `000000003_multi` = 2.08052, `000000004_multi` = 2.53789, `000000005_multi` = 2.12301, `000000006_multi` = 0.594466, `000000007_multi` = 2.36326, `000000008_multi` = 1.52539, `000000009_multi` = 1.4663, `000000010_multi` = 2.90171, `000000011_multi` = 1.25871, `000000012_multi` = 1.24921, `000000013_multi` = 1.15486, `000000014_multi` = 2.20717, `000000015_multi` = 2.0311, `000000016_multi` = 2.02475, `000000017_multi` = 1.47116, `000000018_multi` = 1.20611, `000000019_multi` = 1.64372, `000000020_multi` = 1.12373, `000000021_multi` = 1.44884, `000000022_multi` = 1.88825, `000000023_multi` = 1.35736, `000000024_multi` = 1.18551, `000000025_multi` = 3.19107, `000000026_multi` = 2.1446, `000000027_multi` = 1.9026, `000000028_multi` = 1.58645, `000000029_multi` = 1.54455, `000000030_multi` = 1.50489, `000000031_multi` = 1.16407, `000000032_multi` = 1.78667, `000000033_multi` = 1.1176, `000000034_multi` = 1.80585, `000000035_multi` = 1.95938, `000000036_multi` = 1.1355, `000000037_multi` = 1.54795, `000000038_multi` = 1.6452, `000000039_multi` = 1.43524, `000000040_multi` = 2.46175, `000000041_multi` = 1.35685, `000000042_multi` = 3.28089, `000000043_multi` = 2.65472, `000000044_multi` = 1.09977, `000000045_multi` = 0.643482, `000000046_multi` = 2.17547, `000000047_multi` = 1.51608, `000000048_multi` = 2.14445, `000000049_multi` = 2.25366, `000000050_multi` = 1.65013, `000000051_multi` = 1.39619, `000000052_multi` = 0.997734, `000000053_multi` = 1.4514, `000000054_multi` = 2.00727, `000000055_multi` = 1.41036, `000000056_multi` = 1.01034, `000000057_multi` = 1.55153, `000000058_multi` = 1.73587, `000000059_multi` = 1.65546, `000000060_multi` = 1.9081, `000000061_multi` = 1.24247, `000000062_multi` = 1.0203, `000000063_multi` = 0.916669, `000000064_multi` = 1.88521, `000000065_multi` = 1.24127, `000000066_multi` = 1.93069, `000000067_multi` = 1.6957, `000000068_multi` = 1.34166, `000000069_multi` = 0.927584, `000000070_multi` = 1.76922, `000000071_multi` = 1.82751, `000000072_multi` = 1.71645, `000000073_multi` = 2.21984, `000000074_multi` = 1.88269, `000000075_multi` = 1.03368, `000000076_multi` = 1.37501, `000000077_multi` = 2.64563, `000000078_multi` = 1.81289, `000000079_multi` = 2.16417, `000000080_multi` = 1.32974, `000000081_multi` = 1.40577, `000000082_multi` = 2.18211, `000000083_multi` = 3.00167, `000000084_multi` = 1.88522, `000000085_multi` = 1.57574, `000000086_multi` = 2.32654, `000000087_multi` = 1.65958, `000000088_multi` = 2.47507, `000000089_multi` = 1.29989, `000000090_multi` = 1.77761, `000000091_multi` = 1.90183, `000000092_multi` = 2.06413, `000000093_multi` = 2.5354, `000000094_multi` = 1.84156, `000000095_multi` = 2.48379, `000000096_multi` = 1.32366, `000000097_multi` = 1.79192, `000000098_multi` = 1.46451, `000000099_multi` = 1.64755, `000000100_multi` = 1.40724)" -average,10,2.6206,0.716272,1.55146,4.3116,1,parametric,100,1,"c(`000000001_multi` = 1.82402, `000000002_multi` = 2.32698, `000000003_multi` = 3.22591, `000000004_multi` = 3.64992, `000000005_multi` = 3.10778, `000000006_multi` = 1.16191, `000000007_multi` = 3.52108, `000000008_multi` = 2.29987, `000000009_multi` = 2.37396, `000000010_multi` = 4.07895, `000000011_multi` = 2.01552, `000000012_multi` = 1.9723, `000000013_multi` = 1.93611, `000000014_multi` = 3.24353, `000000015_multi` = 3.09525, `000000016_multi` = 3.04169, `000000017_multi` = 2.29105, `000000018_multi` = 1.98955, +average,0.1,2.6206,0.716272,1.55146,4.3116,1,parametric,100,1,"c(`000000001_multi` = 1.82402, `000000002_multi` = 2.32698, `000000003_multi` = 3.22591, `000000004_multi` = 3.64992, `000000005_multi` = 3.10778, `000000006_multi` = 1.16191, `000000007_multi` = 3.52108, `000000008_multi` = 2.29987, `000000009_multi` = 2.37396, `000000010_multi` = 4.07895, `000000011_multi` = 2.01552, `000000012_multi` = 1.9723, `000000013_multi` = 1.93611, `000000014_multi` = 3.24353, `000000015_multi` = 3.09525, `000000016_multi` = 3.04169, `000000017_multi` = 2.29105, `000000018_multi` = 1.98955, `000000019_multi` = 2.607, `000000020_multi` = 1.80894, `000000021_multi` = 2.19029, `000000022_multi` = 2.89538, `000000023_multi` = 2.13979, `000000024_multi` = 1.86534, `000000025_multi` = 4.78971, `000000026_multi` = 2.95229, `000000027_multi` = 2.96664, `000000028_multi` = 2.52057, `000000029_multi` = 2.3853, `000000030_multi` = 2.37174, `000000031_multi` = 1.77223, `000000032_multi` = 2.8325, `000000033_multi` = 1.7293, `000000034_multi` = 2.89062, `000000035_multi` = 2.81184, `000000036_multi` = 1.77005, `000000037_multi` = 2.4342, `000000038_multi` = 2.55564, `000000039_multi` = 2.33062, `000000040_multi` = 3.70623, `000000041_multi` = 2.1115, `000000042_multi` = 4.58723, `000000043_multi` = 3.94689, `000000044_multi` = 1.79426, `000000045_multi` = 1.23642, `000000046_multi` = 3.38106, `000000047_multi` = 2.54854, `000000048_multi` = 3.18268, `000000049_multi` = 3.43254, `000000050_multi` = 2.46235, `000000051_multi` = 2.30611, `000000052_multi` = 1.66493, `000000053_multi` = 2.45862, `000000054_multi` = 3.30073, `000000055_multi` = 2.26193, `000000056_multi` = 1.56457, `000000057_multi` = 2.64729, `000000058_multi` = 2.9112, `000000059_multi` = 2.58855, `000000060_multi` = 3.01313, `000000061_multi` = 2.04336, `000000062_multi` = 1.6123, `000000063_multi` = 1.82995, `000000064_multi` = 2.97823, `000000065_multi` = 2.01762, `000000066_multi` = 3.08397, `000000067_multi` = 2.63014, `000000068_multi` = 2.10574, `000000069_multi` = 1.53959, `000000070_multi` = 2.75803, `000000071_multi` = 2.9988, `000000072_multi` = 2.53558, diff --git a/tests/testthat/_snaps/hc/hc_notallestimates.csv b/tests/testthat/_snaps/hc/hc_notallestimates.csv index f79179462..588bbc8a8 100644 --- a/tests/testthat/_snaps/hc/hc_notallestimates.csv +++ b/tests/testthat/_snaps/hc/hc_notallestimates.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.64901,0.38467,1.3631,2.46218,1,parametric,10,0.9,"c(`000000001_multi` = 1.61021, `000000002_multi` = 2.30793, `000000003_multi` = 1.80507, `000000004_multi` = 1.97795, `000000005_multi` = 1.40446, `000000006_multi` = 2.50075, `000000007_multi` = 1.88642, `000000009_multi` = 1.67857, `000000010_multi` = 1.35275)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.64901,0.38467,1.3631,2.46218,1,parametric,10,0.9,"c(`000000001_multi` = 1.61021, `000000002_multi` = 2.30793, `000000003_multi` = 1.80507, `000000004_multi` = 1.97795, `000000005_multi` = 1.40446, `000000006_multi` = 2.50075, `000000007_multi` = 1.88642, `000000009_multi` = 1.67857, `000000010_multi` = 1.35275)" diff --git a/tests/testthat/_snaps/hc/hc_para_small.csv b/tests/testthat/_snaps/hc/hc_para_small.csv index b2605b86e..abb980a11 100644 --- a/tests/testthat/_snaps/hc/hc_para_small.csv +++ b/tests/testthat/_snaps/hc/hc_para_small.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -invpareto,5,0.386944,0.347873,0.195882,1.10643,1,non-parametric,10,1,"c(`000000001_invpareto` = 0.982745, `000000002_invpareto` = 0.93683, `000000003_invpareto` = 0.178607, `000000004_invpareto` = 0.292255, `000000005_invpareto` = 0.410782, `000000006_invpareto` = 0.342529, `000000007_invpareto` = 0.255384, `000000008_invpareto` = 1.14234, `000000009_invpareto` = 0.339202, `000000010_invpareto` = 0.476697)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +invpareto,0.05,0.386944,0.347873,0.195882,1.10643,1,non-parametric,10,1,"c(`000000001_invpareto` = 0.982745, `000000002_invpareto` = 0.93683, `000000003_invpareto` = 0.178607, `000000004_invpareto` = 0.292255, `000000005_invpareto` = 0.410782, `000000006_invpareto` = 0.342529, `000000007_invpareto` = 0.255384, `000000008_invpareto` = 1.14234, `000000009_invpareto` = 0.339202, `000000010_invpareto` = 0.476697)" diff --git a/tests/testthat/_snaps/hc/hc_save_to.csv b/tests/testthat/_snaps/hc/hc_save_to.csv index 44e2d8d34..2f1d02a7a 100644 --- a/tests/testthat/_snaps/hc/hc_save_to.csv +++ b/tests/testthat/_snaps/hc/hc_save_to.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68117,0.515645,1.13096,2.11007,1,parametric,3,1,"c(`000000001_multi` = 1.10678, `000000002_multi` = 1.59039, `000000003_multi` = 2.13742)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68117,0.515645,1.13096,2.11007,1,parametric,3,1,"c(`000000001_multi` = 1.10678, `000000002_multi` = 1.59039, `000000003_multi` = 2.13742)" diff --git a/tests/testthat/_snaps/hc/hc_save_to1.csv b/tests/testthat/_snaps/hc/hc_save_to1.csv index 44e2d8d34..2f1d02a7a 100644 --- a/tests/testthat/_snaps/hc/hc_save_to1.csv +++ b/tests/testthat/_snaps/hc/hc_save_to1.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68117,0.515645,1.13096,2.11007,1,parametric,3,1,"c(`000000001_multi` = 1.10678, `000000002_multi` = 1.59039, `000000003_multi` = 2.13742)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68117,0.515645,1.13096,2.11007,1,parametric,3,1,"c(`000000001_multi` = 1.10678, `000000002_multi` = 1.59039, `000000003_multi` = 2.13742)" diff --git a/tests/testthat/_snaps/hc/hc_save_to11.csv b/tests/testthat/_snaps/hc/hc_save_to11.csv index b4d397afa..567508c48 100644 --- a/tests/testthat/_snaps/hc/hc_save_to11.csv +++ b/tests/testthat/_snaps/hc/hc_save_to11.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68117,NA,1.10678,1.10678,1,parametric,1,1,c(`000000001_multi` = 1.10678) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68117,NA,1.10678,1.10678,1,parametric,1,1,c(`000000001_multi` = 1.10678) diff --git a/tests/testthat/_snaps/hc/hc_save_to1_not_multi.csv b/tests/testthat/_snaps/hc/hc_save_to1_not_multi.csv index aefe09e67..84af94920 100644 --- a/tests/testthat/_snaps/hc/hc_save_to1_not_multi.csv +++ b/tests/testthat/_snaps/hc/hc_save_to1_not_multi.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68117,0.52617,1.30753,2.28691,1,parametric,3,1,"c(`000000001_lnorm` = 1.29091, `000000002_lnorm` = 2.32183, `000000003_lnorm` = 1.62344)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68117,0.52617,1.30753,2.28691,1,parametric,3,1,"c(`000000001_lnorm` = 1.29091, `000000002_lnorm` = 2.32183, `000000003_lnorm` = 1.62344)" diff --git a/tests/testthat/_snaps/hc/hc_save_to1_not_multi_default.csv b/tests/testthat/_snaps/hc/hc_save_to1_not_multi_default.csv index 3fc4e1fe5..a4353e704 100644 --- a/tests/testthat/_snaps/hc/hc_save_to1_not_multi_default.csv +++ b/tests/testthat/_snaps/hc/hc_save_to1_not_multi_default.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.24152,NA,1.62613,1.62613,1,parametric,1,1,"c(`000000001_gamma` = 0.987785, `000000001_lgumbel` = 2.2833, `000000001_llogis` = 0.751505, `000000001_lnorm` = 3.09183, `000000001_lnorm_lnorm` = 1.64166, `000000001_weibull` = 1.67077)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.24152,NA,1.62613,1.62613,1,parametric,1,1,"c(`000000001_gamma` = 0.987785, `000000001_lgumbel` = 2.2833, `000000001_llogis` = 0.751505, `000000001_lnorm` = 3.09183, `000000001_lnorm_lnorm` = 1.64166, `000000001_weibull` = 1.67077)" diff --git a/tests/testthat/_snaps/hc/hc_save_to1_rescale.csv b/tests/testthat/_snaps/hc/hc_save_to1_rescale.csv index 44e2d8d34..2f1d02a7a 100644 --- a/tests/testthat/_snaps/hc/hc_save_to1_rescale.csv +++ b/tests/testthat/_snaps/hc/hc_save_to1_rescale.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68117,0.515645,1.13096,2.11007,1,parametric,3,1,"c(`000000001_multi` = 1.10678, `000000002_multi` = 1.59039, `000000003_multi` = 2.13742)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68117,0.515645,1.13096,2.11007,1,parametric,3,1,"c(`000000001_multi` = 1.10678, `000000002_multi` = 1.59039, `000000003_multi` = 2.13742)" diff --git a/tests/testthat/_snaps/hc/hc_save_to1data.csv b/tests/testthat/_snaps/hc/hc_save_to1data.csv index 44e2d8d34..2f1d02a7a 100644 --- a/tests/testthat/_snaps/hc/hc_save_to1data.csv +++ b/tests/testthat/_snaps/hc/hc_save_to1data.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68117,0.515645,1.13096,2.11007,1,parametric,3,1,"c(`000000001_multi` = 1.10678, `000000002_multi` = 1.59039, `000000003_multi` = 2.13742)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68117,0.515645,1.13096,2.11007,1,parametric,3,1,"c(`000000001_multi` = 1.10678, `000000002_multi` = 1.59039, `000000003_multi` = 2.13742)" diff --git a/tests/testthat/_snaps/hc/hc_save_to_not_multi.csv b/tests/testthat/_snaps/hc/hc_save_to_not_multi.csv index aefe09e67..84af94920 100644 --- a/tests/testthat/_snaps/hc/hc_save_to_not_multi.csv +++ b/tests/testthat/_snaps/hc/hc_save_to_not_multi.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68117,0.52617,1.30753,2.28691,1,parametric,3,1,"c(`000000001_lnorm` = 1.29091, `000000002_lnorm` = 2.32183, `000000003_lnorm` = 1.62344)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68117,0.52617,1.30753,2.28691,1,parametric,3,1,"c(`000000001_lnorm` = 1.29091, `000000002_lnorm` = 2.32183, `000000003_lnorm` = 1.62344)" diff --git a/tests/testthat/_snaps/hc/hc_save_to_not_multi_default.csv b/tests/testthat/_snaps/hc/hc_save_to_not_multi_default.csv index 3fc4e1fe5..a4353e704 100644 --- a/tests/testthat/_snaps/hc/hc_save_to_not_multi_default.csv +++ b/tests/testthat/_snaps/hc/hc_save_to_not_multi_default.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.24152,NA,1.62613,1.62613,1,parametric,1,1,"c(`000000001_gamma` = 0.987785, `000000001_lgumbel` = 2.2833, `000000001_llogis` = 0.751505, `000000001_lnorm` = 3.09183, `000000001_lnorm_lnorm` = 1.64166, `000000001_weibull` = 1.67077)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.24152,NA,1.62613,1.62613,1,parametric,1,1,"c(`000000001_gamma` = 0.987785, `000000001_lgumbel` = 2.2833, `000000001_llogis` = 0.751505, `000000001_lnorm` = 3.09183, `000000001_lnorm_lnorm` = 1.64166, `000000001_weibull` = 1.67077)" diff --git a/tests/testthat/_snaps/hc/hc_save_to_rescale.csv b/tests/testthat/_snaps/hc/hc_save_to_rescale.csv index 44e2d8d34..2f1d02a7a 100644 --- a/tests/testthat/_snaps/hc/hc_save_to_rescale.csv +++ b/tests/testthat/_snaps/hc/hc_save_to_rescale.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68117,0.515645,1.13096,2.11007,1,parametric,3,1,"c(`000000001_multi` = 1.10678, `000000002_multi` = 1.59039, `000000003_multi` = 2.13742)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68117,0.515645,1.13096,2.11007,1,parametric,3,1,"c(`000000001_multi` = 1.10678, `000000002_multi` = 1.59039, `000000003_multi` = 2.13742)" diff --git a/tests/testthat/_snaps/hc/hc_unfix.csv b/tests/testthat/_snaps/hc/hc_unfix.csv index 9e2165e68..418fbfb7a 100644 --- a/tests/testthat/_snaps/hc/hc_unfix.csv +++ b/tests/testthat/_snaps/hc/hc_unfix.csv @@ -1,5 +1,5 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68947,0.59232,1.02257,3.29179,1,parametric,100,1,"c(`000000001_multi` = 1.45262, `000000002_multi` = 1.58556, `000000003_multi` = 3.24936, `000000004_multi` = 3.21476, `000000005_multi` = 2.15219, `000000006_multi` = 1.20479, `000000007_multi` = 2.37592, `000000008_multi` = 1.86562, `000000009_multi` = 2.30867, `000000010_multi` = 3.41163, `000000011_multi` = 1.2597, `000000012_multi` = 1.4002, `000000013_multi` = 1.16298, `000000014_multi` = 2.21334, `000000015_multi` = 2.03861, `000000016_multi` = 2.02795, `000000017_multi` = 1.58608, `000000018_multi` = 1.21924, +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68947,0.59232,1.02257,3.29179,1,parametric,100,1,"c(`000000001_multi` = 1.45262, `000000002_multi` = 1.58556, `000000003_multi` = 3.24936, `000000004_multi` = 3.21476, `000000005_multi` = 2.15219, `000000006_multi` = 1.20479, `000000007_multi` = 2.37592, `000000008_multi` = 1.86562, `000000009_multi` = 2.30867, `000000010_multi` = 3.41163, `000000011_multi` = 1.2597, `000000012_multi` = 1.4002, `000000013_multi` = 1.16298, `000000014_multi` = 2.21334, `000000015_multi` = 2.03861, `000000016_multi` = 2.02795, `000000017_multi` = 1.58608, `000000018_multi` = 1.21924, `000000019_multi` = 1.98269, `000000020_multi` = 1.25104, `000000021_multi` = 1.75649, `000000022_multi` = 1.93251, `000000023_multi` = 1.35672, `000000024_multi` = 1.203, `000000025_multi` = 3.20701, `000000026_multi` = 2.14475, `000000027_multi` = 1.91108, `000000028_multi` = 1.75643, `000000029_multi` = 1.62451, `000000030_multi` = 1.50484, `000000031_multi` = 1.20254, `000000032_multi` = 2.04424, `000000033_multi` = 1.1576, `000000034_multi` = 2.18345, `000000035_multi` = 1.97292, `000000036_multi` = 1.17296, `000000037_multi` = 1.77922, `000000038_multi` = 1.75525, `000000039_multi` = 1.43666, `000000040_multi` = 2.60677, `000000041_multi` = 1.36858, `000000042_multi` = 3.33018, `000000043_multi` = 2.6593, `000000044_multi` = 1.11495, `000000045_multi` = 0.644645, `000000046_multi` = 2.25289, `000000047_multi` = 1.78444, `000000048_multi` = 2.15256, `000000049_multi` = 3.39668, `000000050_multi` = 1.64949, `000000051_multi` = 1.49384, `000000052_multi` = 0.998233, `000000053_multi` = 1.49073, `000000054_multi` = 2.01825, `000000055_multi` = 1.54084, `000000056_multi` = 1.01562, `000000057_multi` = 1.91903, `000000058_multi` = 2.20484, `000000059_multi` = 1.70217, `000000060_multi` = 2.41098, `000000061_multi` = 1.70376, `000000062_multi` = 1.03025, `000000063_multi` = 1.76254, `000000064_multi` = 2.56699, `000000065_multi` = 1.38514, `000000066_multi` = 1.99688, `000000067_multi` = 1.73916, `000000068_multi` = 1.38247, `000000069_multi` = 1.50739, `000000070_multi` = 1.77171, `000000071_multi` = 1.8424, `000000072_multi` = 1.72608, diff --git a/tests/testthat/_snaps/hc/hc_unfixmulti.csv b/tests/testthat/_snaps/hc/hc_unfixmulti.csv index 5ed3e2e0e..bb22a3dc3 100644 --- a/tests/testthat/_snaps/hc/hc_unfixmulti.csv +++ b/tests/testthat/_snaps/hc/hc_unfixmulti.csv @@ -1,11 +1,11 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68947,0.59232,1.02257,3.29179,1,parametric,100,1,"c(`000000001_multi` = 1.45262, `000000002_multi` = 1.58556, `000000003_multi` = 3.24936, `000000004_multi` = 3.21476, `000000005_multi` = 2.15219, `000000006_multi` = 1.20479, `000000007_multi` = 2.37592, `000000008_multi` = 1.86562, `000000009_multi` = 2.30867, `000000010_multi` = 3.41163, `000000011_multi` = 1.2597, `000000012_multi` = 1.4002, `000000013_multi` = 1.16298, `000000014_multi` = 2.21334, `000000015_multi` = 2.03861, `000000016_multi` = 2.02795, `000000017_multi` = 1.58608, `000000018_multi` = 1.21924, +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68947,0.59232,1.02257,3.29179,1,parametric,100,1,"c(`000000001_multi` = 1.45262, `000000002_multi` = 1.58556, `000000003_multi` = 3.24936, `000000004_multi` = 3.21476, `000000005_multi` = 2.15219, `000000006_multi` = 1.20479, `000000007_multi` = 2.37592, `000000008_multi` = 1.86562, `000000009_multi` = 2.30867, `000000010_multi` = 3.41163, `000000011_multi` = 1.2597, `000000012_multi` = 1.4002, `000000013_multi` = 1.16298, `000000014_multi` = 2.21334, `000000015_multi` = 2.03861, `000000016_multi` = 2.02795, `000000017_multi` = 1.58608, `000000018_multi` = 1.21924, `000000019_multi` = 1.98269, `000000020_multi` = 1.25104, `000000021_multi` = 1.75649, `000000022_multi` = 1.93251, `000000023_multi` = 1.35672, `000000024_multi` = 1.203, `000000025_multi` = 3.20701, `000000026_multi` = 2.14475, `000000027_multi` = 1.91108, `000000028_multi` = 1.75643, `000000029_multi` = 1.62451, `000000030_multi` = 1.50484, `000000031_multi` = 1.20254, `000000032_multi` = 2.04424, `000000033_multi` = 1.1576, `000000034_multi` = 2.18345, `000000035_multi` = 1.97292, `000000036_multi` = 1.17296, `000000037_multi` = 1.77922, `000000038_multi` = 1.75525, `000000039_multi` = 1.43666, `000000040_multi` = 2.60677, `000000041_multi` = 1.36858, `000000042_multi` = 3.33018, `000000043_multi` = 2.6593, `000000044_multi` = 1.11495, `000000045_multi` = 0.644645, `000000046_multi` = 2.25289, `000000047_multi` = 1.78444, `000000048_multi` = 2.15256, `000000049_multi` = 3.39668, `000000050_multi` = 1.64949, `000000051_multi` = 1.49384, `000000052_multi` = 0.998233, `000000053_multi` = 1.49073, `000000054_multi` = 2.01825, `000000055_multi` = 1.54084, `000000056_multi` = 1.01562, `000000057_multi` = 1.91903, `000000058_multi` = 2.20484, `000000059_multi` = 1.70217, `000000060_multi` = 2.41098, `000000061_multi` = 1.70376, `000000062_multi` = 1.03025, `000000063_multi` = 1.76254, `000000064_multi` = 2.56699, `000000065_multi` = 1.38514, `000000066_multi` = 1.99688, `000000067_multi` = 1.73916, `000000068_multi` = 1.38247, `000000069_multi` = 1.50739, `000000070_multi` = 1.77171, `000000071_multi` = 1.8424, `000000072_multi` = 1.72608, `000000073_multi` = 2.799, `000000074_multi` = 1.88272, `000000075_multi` = 1.05176, `000000076_multi` = 1.40962, `000000077_multi` = 2.96666, `000000078_multi` = 1.86154, `000000079_multi` = 2.29813, `000000080_multi` = 2.10876, `000000081_multi` = 1.82325, `000000082_multi` = 2.26361, `000000083_multi` = 3.00163, `000000084_multi` = 1.89377, `000000085_multi` = 1.6872, `000000086_multi` = 2.3597, `000000087_multi` = 1.79505, `000000088_multi` = 2.88804, `000000089_multi` = 1.31556, `000000090_multi` = 1.8439, `000000091_multi` = 1.90107, `000000092_multi` = 2.3051, `000000093_multi` = 2.57291, `000000094_multi` = 1.86754, `000000095_multi` = 2.79026, `000000096_multi` = 1.342, `000000097_multi` = 1.80368, `000000098_multi` = 1.46857, `000000099_multi` = 1.9727, `000000100_multi` = 2.03696)" -average,10,2.6206,0.741085,1.65498,4.39448,1,parametric,100,1,"c(`000000001_multi` = 2.0653, `000000002_multi` = 2.32151, `000000003_multi` = 4.1392, `000000004_multi` = 4.09275, `000000005_multi` = 3.10275, `000000006_multi` = 1.7419, `000000007_multi` = 3.51008, `000000008_multi` = 2.5101, `000000009_multi` = 3.04733, `000000010_multi` = 4.37277, `000000011_multi` = 2.02624, `000000012_multi` = 2.04602, `000000013_multi` = 1.92981, `000000014_multi` = 3.27117, `000000015_multi` = 3.12353, `000000016_multi` = 3.06158, `000000017_multi` = 2.33394, `000000018_multi` = 1.98309, +average,0.1,2.6206,0.741085,1.65498,4.39448,1,parametric,100,1,"c(`000000001_multi` = 2.0653, `000000002_multi` = 2.32151, `000000003_multi` = 4.1392, `000000004_multi` = 4.09275, `000000005_multi` = 3.10275, `000000006_multi` = 1.7419, `000000007_multi` = 3.51008, `000000008_multi` = 2.5101, `000000009_multi` = 3.04733, `000000010_multi` = 4.37277, `000000011_multi` = 2.02624, `000000012_multi` = 2.04602, `000000013_multi` = 1.92981, `000000014_multi` = 3.27117, `000000015_multi` = 3.12353, `000000016_multi` = 3.06158, `000000017_multi` = 2.33394, `000000018_multi` = 1.98309, `000000019_multi` = 2.81331, `000000020_multi` = 1.86874, `000000021_multi` = 2.37771, `000000022_multi` = 2.89637, `000000023_multi` = 2.14424, `000000024_multi` = 1.86082, `000000025_multi` = 4.77609, `000000026_multi` = 2.9607, `000000027_multi` = 2.95928, `000000028_multi` = 2.59848, `000000029_multi` = 2.40736, `000000030_multi` = 2.37186, `000000031_multi` = 1.77782, `000000032_multi` = 2.96954, `000000033_multi` = 1.73585, `000000034_multi` = 3.12053, `000000035_multi` = 2.84466, `000000036_multi` = 1.77466, `000000037_multi` = 2.55891, `000000038_multi` = 2.59334, `000000039_multi` = 2.34664, `000000040_multi` = 3.7501, `000000041_multi` = 2.10563, `000000042_multi` = 4.58074, `000000043_multi` = 3.94081, `000000044_multi` = 1.78813, `000000045_multi` = 1.24824, `000000046_multi` = 3.38999, `000000047_multi` = 2.70451, `000000048_multi` = 3.17522, `000000049_multi` = 4.30121, `000000050_multi` = 2.46468, `000000051_multi` = 2.33762, `000000052_multi` = 1.67442, `000000053_multi` = 2.45527, `000000054_multi` = 3.29217, `000000055_multi` = 2.31535, `000000056_multi` = 1.56046, `000000057_multi` = 2.88259, `000000058_multi` = 3.22329, `000000059_multi` = 2.59144, `000000060_multi` = 3.34163, `000000061_multi` = 2.37449, `000000062_multi` = 1.63739, `000000063_multi` = 2.62527, `000000064_multi` = 3.46001, `000000065_multi` = 2.08574, `000000066_multi` = 3.09123, `000000067_multi` = 2.63002, `000000068_multi` = 2.10855, `000000069_multi` = 2.0103, `000000070_multi` = 2.75425, `000000071_multi` = 2.98879, `000000072_multi` = 2.52871, diff --git a/tests/testthat/_snaps/hc/hc_unweighted2.csv b/tests/testthat/_snaps/hc/hc_unweighted2.csv index 52156d530..c25d77b30 100644 --- a/tests/testthat/_snaps/hc/hc_unweighted2.csv +++ b/tests/testthat/_snaps/hc/hc_unweighted2.csv @@ -1,5 +1,5 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,samples -average,5,1.24152,0.886733,0.806142,3.20382,1,parametric,10,"c(`000000001_gamma` = 0.987785, `000000002_gamma` = 3.15112, `000000003_gamma` = 0.84656, `000000004_gamma` = 0.70604, `000000005_gamma` = 1.98672, `000000006_gamma` = 0.873452, `000000007_gamma` = 1.18798, `000000008_gamma` = 0.836688, `000000009_gamma` = 0.719689, `000000010_gamma` = 3.20738, `000000001_lgumbel` = 2.2833, `000000002_lgumbel` = 1.48094, `000000003_lgumbel` = 2.12922, `000000004_lgumbel` = 2.36856, `000000005_lgumbel` = 1.81154, `000000006_lgumbel` = 1.96535, `000000007_lgumbel` = 1.36401, +dist,proportion,est,se,lcl,ucl,wt,method,nboot,samples +average,0.05,1.24152,0.886733,0.806142,3.20382,1,parametric,10,"c(`000000001_gamma` = 0.987785, `000000002_gamma` = 3.15112, `000000003_gamma` = 0.84656, `000000004_gamma` = 0.70604, `000000005_gamma` = 1.98672, `000000006_gamma` = 0.873452, `000000007_gamma` = 1.18798, `000000008_gamma` = 0.836688, `000000009_gamma` = 0.719689, `000000010_gamma` = 3.20738, `000000001_lgumbel` = 2.2833, `000000002_lgumbel` = 1.48094, `000000003_lgumbel` = 2.12922, `000000004_lgumbel` = 2.36856, `000000005_lgumbel` = 1.81154, `000000006_lgumbel` = 1.96535, `000000007_lgumbel` = 1.36401, `000000008_lgumbel` = 1.93797, `000000009_lgumbel` = 2.70632, `000000010_lgumbel` = 2.09232, `000000001_llogis` = 0.751505, `000000002_llogis` = 3.04268, `000000003_llogis` = 2.10953, `000000004_llogis` = 2.22634, `000000005_llogis` = 1.30249, `000000006_llogis` = 2.52802, `000000007_llogis` = 3.46857, `000000008_llogis` = 2.04533, `000000009_llogis` = 1.85618, `000000010_llogis` = 1.19654, `000000001_lnorm` = 3.09183, `000000002_lnorm` = 2.42899, `000000003_lnorm` = 1.325, `000000004_lnorm` = 1.61081, `000000005_lnorm` = 2.60329, `000000006_lnorm` = 0.865973, `000000007_lnorm` = 2.77742, `000000008_lnorm` = 1.19715, `000000009_lnorm` = 2.45546, `000000010_lnorm` = 0.970094, `000000001_lnorm_lnorm` = 1.64166, `000000002_lnorm_lnorm` = 1.67909, `000000003_lnorm_lnorm` = 1.80876, `000000004_lnorm_lnorm` = 0.921821, `000000005_lnorm_lnorm` = 1.68365, `000000006_lnorm_lnorm` = 1.28523, `000000007_lnorm_lnorm` = 1.82578, `000000008_lnorm_lnorm` = 1.05663, `000000009_lnorm_lnorm` = 1.20995, `000000010_lnorm_lnorm` = 1.67578, `000000001_weibull` = 1.67077, `000000002_weibull` = 0.93999, `000000003_weibull` = 1.45323, `000000004_weibull` = 3.60435, `000000005_weibull` = 1.0464, `000000006_weibull` = 1.48364, `000000007_weibull` = 2.08463, `000000008_weibull` = 1.05416, `000000009_weibull` = 2.73428, `000000010_weibull` = 0.784157)" diff --git a/tests/testthat/_snaps/hc/hc_weighted2.csv b/tests/testthat/_snaps/hc/hc_weighted2.csv index 799a84274..b25ed385b 100644 --- a/tests/testthat/_snaps/hc/hc_weighted2.csv +++ b/tests/testthat/_snaps/hc/hc_weighted2.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,samples -average,5,1.24152,0.875982,0.702735,3.12015,1,parametric,10,"c(`000000001_gamma` = 0.987785, `000000002_gamma` = 3.15112, `000000003_gamma` = 0.84656, `000000004_gamma` = 0.70604, `000000001_llogis` = 1.80721, `000000001_lnorm` = 0.921872, `000000002_lnorm` = 1.73558, `000000001_weibull` = 1.97675, `000000002_weibull` = 0.701634, `000000003_weibull` = 1.43587, `000000004_weibull` = 3.02724)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,samples +average,0.05,1.24152,0.875982,0.702735,3.12015,1,parametric,10,"c(`000000001_gamma` = 0.987785, `000000002_gamma` = 3.15112, `000000003_gamma` = 0.84656, `000000004_gamma` = 0.70604, `000000001_llogis` = 1.80721, `000000001_lnorm` = 0.921872, `000000002_lnorm` = 1.73558, `000000001_weibull` = 1.97675, `000000002_weibull` = 0.701634, `000000003_weibull` = 1.43587, `000000004_weibull` = 3.02724)" diff --git a/tests/testthat/_snaps/hc/hc_weighted_bootstrap.csv b/tests/testthat/_snaps/hc/hc_weighted_bootstrap.csv index 9f87e9127..785e23eea 100644 --- a/tests/testthat/_snaps/hc/hc_weighted_bootstrap.csv +++ b/tests/testthat/_snaps/hc/hc_weighted_bootstrap.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.27578,0.569544,0.492722,2.16469,1,parametric,10,1,"c(`000000001_lnorm` = 1.29091, `000000002_lnorm` = 2.32183, `000000003_lnorm` = 1.62344, `000000001_gamma` = 0.508842, `000000002_gamma` = 1.14031, `000000003_gamma` = 0.859883, `000000004_gamma` = 0.65392, `000000005_gamma` = 0.488042, `000000006_gamma` = 1.15914, `000000007_gamma` = 0.732169)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.27578,0.569544,0.492722,2.16469,1,parametric,10,1,"c(`000000001_lnorm` = 1.29091, `000000002_lnorm` = 2.32183, `000000003_lnorm` = 1.62344, `000000001_gamma` = 0.508842, `000000002_gamma` = 1.14031, `000000003_gamma` = 0.859883, `000000004_gamma` = 0.65392, `000000005_gamma` = 0.488042, `000000006_gamma` = 1.15914, `000000007_gamma` = 0.732169)" diff --git a/tests/testthat/_snaps/hc/hcici.csv b/tests/testthat/_snaps/hc/hcici.csv index 2959fc036..9dbb075d8 100644 --- a/tests/testthat/_snaps/hc/hcici.csv +++ b/tests/testthat/_snaps/hc/hcici.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68117,0.455819,0.998397,2.43078,1,parametric,10,1,"c(`000000001_lnorm` = 0.934605, `000000002_lnorm` = 1.21812, `000000003_lnorm` = 1.45944, `000000004_lnorm` = 1.76622, `000000005_lnorm` = 1.65194, `000000006_lnorm` = 1.84673, `000000007_lnorm` = 1.60237, `000000008_lnorm` = 2.28776, `000000009_lnorm` = 2.4723, `000000010_lnorm` = 1.56512)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68117,0.455819,0.998397,2.43078,1,parametric,10,1,"c(`000000001_lnorm` = 0.934605, `000000002_lnorm` = 1.21812, `000000003_lnorm` = 1.45944, `000000004_lnorm` = 1.76622, `000000005_lnorm` = 1.65194, `000000006_lnorm` = 1.84673, `000000007_lnorm` = 1.60237, `000000008_lnorm` = 2.28776, `000000009_lnorm` = 2.4723, `000000010_lnorm` = 1.56512)" diff --git a/tests/testthat/_snaps/hc/hcici_multi.csv b/tests/testthat/_snaps/hc/hcici_multi.csv index 2959fc036..9dbb075d8 100644 --- a/tests/testthat/_snaps/hc/hcici_multi.csv +++ b/tests/testthat/_snaps/hc/hcici_multi.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.68117,0.455819,0.998397,2.43078,1,parametric,10,1,"c(`000000001_lnorm` = 0.934605, `000000002_lnorm` = 1.21812, `000000003_lnorm` = 1.45944, `000000004_lnorm` = 1.76622, `000000005_lnorm` = 1.65194, `000000006_lnorm` = 1.84673, `000000007_lnorm` = 1.60237, `000000008_lnorm` = 2.28776, `000000009_lnorm` = 2.4723, `000000010_lnorm` = 1.56512)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.68117,0.455819,0.998397,2.43078,1,parametric,10,1,"c(`000000001_lnorm` = 0.934605, `000000002_lnorm` = 1.21812, `000000003_lnorm` = 1.45944, `000000004_lnorm` = 1.76622, `000000005_lnorm` = 1.65194, `000000006_lnorm` = 1.84673, `000000007_lnorm` = 1.60237, `000000008_lnorm` = 2.28776, `000000009_lnorm` = 2.4723, `000000010_lnorm` = 1.56512)" diff --git a/tests/testthat/_snaps/invpareto/hc_boron.csv b/tests/testthat/_snaps/invpareto/hc_boron.csv index 40bdef9ba..1db22525a 100644 --- a/tests/testthat/_snaps/invpareto/hc_boron.csv +++ b/tests/testthat/_snaps/invpareto/hc_boron.csv @@ -1,5 +1,5 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,0.386944,0.399067,0.0653409,1.61932,1,parametric,100,1,"c(`000000001_multi` = 1.56247, `000000002_multi` = 0.400166, `000000003_multi` = 0.253929, `000000004_multi` = 0.256294, `000000005_multi` = 0.501515, `000000006_multi` = 0.288336, `000000007_multi` = 0.195476, `000000008_multi` = 0.323431, `000000009_multi` = 0.377317, `000000010_multi` = 0.458898, `000000011_multi` = 0.306446, `000000012_multi` = 1.02948, `000000013_multi` = 0.493444, `000000014_multi` = 0.248135, `000000015_multi` = 0.223464, `000000016_multi` = 1.0636, `000000017_multi` = 0.50697, +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,0.386944,0.399067,0.0653409,1.61932,1,parametric,100,1,"c(`000000001_multi` = 1.56247, `000000002_multi` = 0.400166, `000000003_multi` = 0.253929, `000000004_multi` = 0.256294, `000000005_multi` = 0.501515, `000000006_multi` = 0.288336, `000000007_multi` = 0.195476, `000000008_multi` = 0.323431, `000000009_multi` = 0.377317, `000000010_multi` = 0.458898, `000000011_multi` = 0.306446, `000000012_multi` = 1.02948, `000000013_multi` = 0.493444, `000000014_multi` = 0.248135, `000000015_multi` = 0.223464, `000000016_multi` = 1.0636, `000000017_multi` = 0.50697, `000000018_multi` = 0.209837, `000000019_multi` = 0.0549665, `000000020_multi` = 0.227692, `000000021_multi` = 0.89167, `000000022_multi` = 0.50649, `000000023_multi` = 0.404041, `000000024_multi` = 0.366847, `000000025_multi` = 0.218858, `000000026_multi` = 0.274032, `000000027_multi` = 0.727305, `000000028_multi` = 0.839638, `000000029_multi` = 0.0298699, `000000030_multi` = 0.82018, `000000031_multi` = 0.305451, `000000032_multi` = 0.272701, `000000033_multi` = 0.23849, `000000034_multi` = 1.26155, `000000035_multi` = 0.160792, `000000036_multi` = 0.26142, `000000037_multi` = 0.620122, `000000038_multi` = 0.381318, `000000039_multi` = 1.67075, `000000040_multi` = 0.378817, `000000041_multi` = 0.338324, `000000042_multi` = 0.653714, `000000043_multi` = 0.078812, `000000044_multi` = 0.369199, `000000045_multi` = 0.18526, `000000046_multi` = 0.236007, `000000047_multi` = 0.822142, `000000048_multi` = 0.765152, `000000049_multi` = 0.893584, `000000050_multi` = 0.275912, `000000051_multi` = 0.625307, `000000052_multi` = 0.716129, `000000053_multi` = 0.506941, `000000054_multi` = 0.0863136, `000000055_multi` = 0.122999, `000000056_multi` = 1.1238, `000000057_multi` = 1.47271, `000000058_multi` = 0.557123, `000000059_multi` = 0.426322, `000000060_multi` = 1.27694, `000000061_multi` = 0.440778, `000000062_multi` = 0.0768074, `000000063_multi` = 1.8385, `000000064_multi` = 0.760694, `000000065_multi` = 0.931577, `000000066_multi` = 0.156017, `000000067_multi` = 0.117414, `000000068_multi` = 0.330591, diff --git a/tests/testthat/_snaps/predict/pred_cis.csv b/tests/testthat/_snaps/predict/pred_cis.csv index 3147e86d1..339332089 100644 --- a/tests/testthat/_snaps/predict/pred_cis.csv +++ b/tests/testthat/_snaps/predict/pred_cis.csv @@ -1,100 +1,100 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,1,0.341191,0.222047,0.152493,0.793526,1,parametric,10,1,numeric(0) -average,2,0.573299,0.34303,0.262086,1.25377,1,parametric,10,1,numeric(0) -average,3,0.797571,0.445753,0.377274,1.66538,1,parametric,10,1,numeric(0) -average,4,1.01963,0.538078,0.499046,2.0510100000000002,1,parametric,10,1,numeric(0) -average,5,1.24152,0.623282,0.625225,2.42089,1,parametric,10,1,numeric(0) -average,6,1.46426,0.703143,0.756963,2.78042,1,parametric,10,1,numeric(0) 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+weibull,0.65,24.7276,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.66,25.4347,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.67,26.1636,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.68,26.9156,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.69,27.6923,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.7,28.4952,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.71,29.3261,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.72,30.187,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.73,31.0802,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.74,32.0079,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.75,32.973,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.76,33.9786,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.77,35.028,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.78,36.1252,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.79,37.2747,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.8,38.4815,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.81,39.7517,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.82,41.092,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.83,42.5106,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.84,44.017,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.85,45.6225,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.86,47.341,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.87,49.1892,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.88,51.1881,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.89,53.364,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.9,55.7509,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.91,58.3935,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.92,61.3525,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.93,64.713,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.94,68.5998,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.95,73.2065,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.96,78.8579,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.97,86.1642,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.98,96.4972,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) +weibull,0.99,114.247,NA,NA,NA,0.357472,parametric,0,NA,numeric(0) diff --git a/tests/testthat/_snaps/schwarz-tillmans/hc.csv b/tests/testthat/_snaps/schwarz-tillmans/hc.csv index 29ec01c72..8a72369d3 100644 --- a/tests/testthat/_snaps/schwarz-tillmans/hc.csv +++ b/tests/testthat/_snaps/schwarz-tillmans/hc.csv @@ -1,7 +1,7 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -gompertz,5,1.29946,NA,NA,NA,0.270604,parametric,0,NA,numeric(0) -weibull,5,1.08673,NA,NA,NA,0.268699,parametric,0,NA,numeric(0) -gamma,5,1.07428,NA,NA,NA,0.268024,parametric,0,NA,numeric(0) -lnorm,5,1.68117,NA,NA,NA,0.133222,parametric,0,NA,numeric(0) -llogis,5,1.56226,NA,NA,NA,0.0493432,parametric,0,NA,numeric(0) -lgumbel,5,1.76939,NA,NA,NA,0.0101073,parametric,0,NA,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +gompertz,0.05,1.29946,NA,NA,NA,0.270604,parametric,0,NA,numeric(0) +weibull,0.05,1.08673,NA,NA,NA,0.268699,parametric,0,NA,numeric(0) +gamma,0.05,1.07428,NA,NA,NA,0.268024,parametric,0,NA,numeric(0) +lnorm,0.05,1.68117,NA,NA,NA,0.133222,parametric,0,NA,numeric(0) +llogis,0.05,1.56226,NA,NA,NA,0.0493432,parametric,0,NA,numeric(0) +lgumbel,0.05,1.76939,NA,NA,NA,0.0101073,parametric,0,NA,numeric(0) diff --git a/tests/testthat/_snaps/schwarz-tillmans/hc_avg.csv b/tests/testthat/_snaps/schwarz-tillmans/hc_avg.csv index ab54ca849..1a9af3a02 100644 --- a/tests/testthat/_snaps/schwarz-tillmans/hc_avg.csv +++ b/tests/testthat/_snaps/schwarz-tillmans/hc_avg.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.25052,NA,NA,NA,1,parametric,0,NA,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.25052,NA,NA,NA,1,parametric,0,NA,numeric(0) diff --git a/tests/testthat/_snaps/ssd-plot/boron_breaks.png b/tests/testthat/_snaps/ssd-plot/boron_breaks.png index 823021588..04c533e85 100644 Binary files a/tests/testthat/_snaps/ssd-plot/boron_breaks.png and b/tests/testthat/_snaps/ssd-plot/boron_breaks.png differ diff --git a/tests/testthat/_snaps/ssd-plot/boron_color.png b/tests/testthat/_snaps/ssd-plot/boron_color.png index d97f85d52..5a40fdbaf 100644 Binary files a/tests/testthat/_snaps/ssd-plot/boron_color.png and b/tests/testthat/_snaps/ssd-plot/boron_color.png differ diff --git a/tests/testthat/_snaps/ssd-plot/boron_pred.png b/tests/testthat/_snaps/ssd-plot/boron_pred.png index 2f08b4ffd..e418c451d 100644 Binary files a/tests/testthat/_snaps/ssd-plot/boron_pred.png and b/tests/testthat/_snaps/ssd-plot/boron_pred.png differ diff --git a/tests/testthat/_snaps/ssd-plot/boron_pred_label.png b/tests/testthat/_snaps/ssd-plot/boron_pred_label.png index 5af3998d1..daabe7ab9 100644 Binary files a/tests/testthat/_snaps/ssd-plot/boron_pred_label.png and b/tests/testthat/_snaps/ssd-plot/boron_pred_label.png differ diff --git a/tests/testthat/_snaps/ssd-plot/boron_pred_shift_x.png b/tests/testthat/_snaps/ssd-plot/boron_pred_shift_x.png index 142115449..79c6a7382 100644 Binary files a/tests/testthat/_snaps/ssd-plot/boron_pred_shift_x.png and b/tests/testthat/_snaps/ssd-plot/boron_pred_shift_x.png differ diff --git a/tests/testthat/_snaps/ssd-plot/boron_shape.png b/tests/testthat/_snaps/ssd-plot/boron_shape.png index 045210841..2bad15a26 100644 Binary files a/tests/testthat/_snaps/ssd-plot/boron_shape.png and b/tests/testthat/_snaps/ssd-plot/boron_shape.png differ diff --git a/tests/testthat/_snaps/ssd-plot/missing_order.png b/tests/testthat/_snaps/ssd-plot/missing_order.png index 095fc58ce..4005825c3 100644 Binary files a/tests/testthat/_snaps/ssd-plot/missing_order.png and b/tests/testthat/_snaps/ssd-plot/missing_order.png differ diff --git a/tests/testthat/_snaps/weibull/hc_anona.csv b/tests/testthat/_snaps/weibull/hc_anona.csv index dbd90aacc..646875e94 100644 --- a/tests/testthat/_snaps/weibull/hc_anona.csv +++ b/tests/testthat/_snaps/weibull/hc_anona.csv @@ -1,5 +1,5 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,6.42593,15.7252,0.700779,53.8366,1,parametric,1000,1,"c(`000000001_weibull` = 19.5331, `000000002_weibull` = 3.50237, `000000003_weibull` = 4.40539, `000000004_weibull` = 8.44417, `000000005_weibull` = 40.9936, `000000006_weibull` = 17.6807, `000000007_weibull` = 5.57319, `000000008_weibull` = 43.9998, `000000009_weibull` = 2.57976, `000000010_weibull` = 5.23002, `000000011_weibull` = 8.07911, `000000012_weibull` = 5.01415, `000000013_weibull` = 4.07884, `000000014_weibull` = 3.04445, `000000015_weibull` = 6.10087, `000000016_weibull` = 2.21551, `000000017_weibull` = 14.4184, +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,6.42593,15.7252,0.700779,53.8366,1,parametric,1000,1,"c(`000000001_weibull` = 19.5331, `000000002_weibull` = 3.50237, `000000003_weibull` = 4.40539, `000000004_weibull` = 8.44417, `000000005_weibull` = 40.9936, `000000006_weibull` = 17.6807, `000000007_weibull` = 5.57319, `000000008_weibull` = 43.9998, `000000009_weibull` = 2.57976, `000000010_weibull` = 5.23002, `000000011_weibull` = 8.07911, `000000012_weibull` = 5.01415, `000000013_weibull` = 4.07884, `000000014_weibull` = 3.04445, `000000015_weibull` = 6.10087, `000000016_weibull` = 2.21551, `000000017_weibull` = 14.4184, `000000018_weibull` = 19.3822, `000000019_weibull` = 8.63474, `000000020_weibull` = 8.64451, `000000021_weibull` = 3.8992, `000000022_weibull` = 15.5584, `000000023_weibull` = 9.03457, `000000024_weibull` = 1.29008, `000000025_weibull` = 22.3785, `000000026_weibull` = 24.1325, `000000027_weibull` = 3.70208, `000000028_weibull` = 11.4905, `000000029_weibull` = 40.4752, `000000030_weibull` = 26.3224, `000000031_weibull` = 22.5898, `000000032_weibull` = 35.578, `000000033_weibull` = 0.763847, `000000034_weibull` = 6.62819, `000000035_weibull` = 5.91055, `000000036_weibull` = 7.85492, `000000037_weibull` = 16.9274, `000000038_weibull` = 13.8314, `000000039_weibull` = 3.60487, `000000040_weibull` = 2.39172, `000000041_weibull` = 7.35896, `000000042_weibull` = 15.659, `000000043_weibull` = 75.3306, `000000044_weibull` = 26.3684, `000000045_weibull` = 22.3269, `000000046_weibull` = 33.0258, `000000047_weibull` = 10.0165, `000000048_weibull` = 2.14456, `000000049_weibull` = 2.60983, `000000050_weibull` = 5.91748, `000000051_weibull` = 16.2137, `000000052_weibull` = 2.84679, `000000053_weibull` = 86.756, `000000054_weibull` = 7.54035, `000000055_weibull` = 3.97361, `000000056_weibull` = 46.5391, `000000057_weibull` = 1.13562, `000000058_weibull` = 9.83459, `000000059_weibull` = 25.256, `000000060_weibull` = 28.5201, `000000061_weibull` = 2.29067, `000000062_weibull` = 2.89851, `000000063_weibull` = 13.054, `000000064_weibull` = 6.09376, `000000065_weibull` = 8.04456, `000000066_weibull` = 6.73045, `000000067_weibull` = 42.9916, `000000068_weibull` = 9.31959, diff --git a/tests/testthat/_snaps/zzz-unstable.md b/tests/testthat/_snaps/zzz-unstable.md index ea139ac4e..ba30db9dc 100644 --- a/tests/testthat/_snaps/zzz-unstable.md +++ b/tests/testthat/_snaps/zzz-unstable.md @@ -4,9 +4,9 @@ hc_average Output # A tibble: 1 x 11 - dist percent est se lcl ucl wt method nboot pboot samples - > - 1 average 5 1.24 0.743 0.479 3.19 1 parametric 100 1 + dist proportion est se lcl ucl wt method nboot pboot samples + + 1 average 0.05 1.24 0.743 0.479 3.19 1 parametr~ 100 1 --- @@ -14,9 +14,9 @@ hc_multi Output # A tibble: 1 x 11 - dist percent est se lcl ucl wt method nboot pboot samples - > - 1 average 5 1.26 0.774 0.410 3.25 1 parametric 100 0.86 + dist proportion est se lcl ucl wt method nboot pboot samples + + 1 average 0.05 1.26 0.774 0.410 3.25 1 parametr~ 100 0.86 # hp multi_ci lnorm default 100 diff --git a/tests/testthat/_snaps/zzz-unstable/boron_cens_pred_ribbon.png b/tests/testthat/_snaps/zzz-unstable/boron_cens_pred_ribbon.png index 63f2806b5..d92ebe313 100644 Binary files a/tests/testthat/_snaps/zzz-unstable/boron_cens_pred_ribbon.png and b/tests/testthat/_snaps/zzz-unstable/boron_cens_pred_ribbon.png differ diff --git a/tests/testthat/_snaps/zzz-unstable/geoms_all.png b/tests/testthat/_snaps/zzz-unstable/geoms_all.png index 516cd7d85..6fbcdb617 100644 Binary files a/tests/testthat/_snaps/zzz-unstable/geoms_all.png and b/tests/testthat/_snaps/zzz-unstable/geoms_all.png differ diff --git a/tests/testthat/_snaps/zzz-unstable/hc_err.csv b/tests/testthat/_snaps/zzz-unstable/hc_err.csv index e03765be3..0cdb26083 100644 --- a/tests/testthat/_snaps/zzz-unstable/hc_err.csv +++ b/tests/testthat/_snaps/zzz-unstable/hc_err.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,0.934681,0.33094,0.839423,2.35185,1,parametric,100,0.97,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,0.934681,0.33094,0.839423,2.35185,1,parametric,100,0.97,numeric(0) diff --git a/tests/testthat/_snaps/zzz-unstable/hc_err_na.csv b/tests/testthat/_snaps/zzz-unstable/hc_err_na.csv index 46141c847..0c498fc25 100644 --- a/tests/testthat/_snaps/zzz-unstable/hc_err_na.csv +++ b/tests/testthat/_snaps/zzz-unstable/hc_err_na.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,0.934681,NA,NA,NA,1,parametric,100,0.94,numeric(0) +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,0.934681,NA,NA,NA,1,parametric,100,0.94,numeric(0) diff --git a/tests/testthat/_snaps/zzz-unstable/hc_nonpara.csv b/tests/testthat/_snaps/zzz-unstable/hc_nonpara.csv index d178a873b..db834eea3 100644 --- a/tests/testthat/_snaps/zzz-unstable/hc_nonpara.csv +++ b/tests/testthat/_snaps/zzz-unstable/hc_nonpara.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.42635,0.0298623,1.37466,1.45809,1,non-parametric,10,1,"c(`000000001_lnorm` = 1.44298, `000000002_lnorm` = 1.3734, `000000003_lnorm` = 1.43012, `000000004_lnorm` = 1.39918, `000000005_lnorm` = 1.40569, `000000006_lnorm` = 1.39248, `000000007_lnorm` = 1.379, `000000008_lnorm` = 1.43881, `000000009_lnorm` = 1.43309, `000000010_lnorm` = 1.46248)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.42635,0.0298623,1.37466,1.45809,1,non-parametric,10,1,"c(`000000001_lnorm` = 1.44298, `000000002_lnorm` = 1.3734, `000000003_lnorm` = 1.43012, `000000004_lnorm` = 1.39918, `000000005_lnorm` = 1.40569, `000000006_lnorm` = 1.39248, `000000007_lnorm` = 1.379, `000000008_lnorm` = 1.43881, `000000009_lnorm` = 1.43309, `000000010_lnorm` = 1.46248)" diff --git a/tests/testthat/_snaps/zzz-unstable/hc_para.csv b/tests/testthat/_snaps/zzz-unstable/hc_para.csv index 020d00c7c..f6301f7c2 100644 --- a/tests/testthat/_snaps/zzz-unstable/hc_para.csv +++ b/tests/testthat/_snaps/zzz-unstable/hc_para.csv @@ -1,2 +1,2 @@ -dist,percent,est,se,lcl,ucl,wt,method,nboot,pboot,samples -average,5,1.42635,0.0143222,1.39439,1.43839,1,parametric,10,1,"c(`000000001_lnorm` = 1.3915, `000000002_lnorm` = 1.42055, `000000003_lnorm` = 1.41287, `000000004_lnorm` = 1.42336, `000000005_lnorm` = 1.42911, `000000006_lnorm` = 1.40433, `000000007_lnorm` = 1.42858, `000000008_lnorm` = 1.44108, `000000009_lnorm` = 1.40699, `000000010_lnorm` = 1.4205)" +dist,proportion,est,se,lcl,ucl,wt,method,nboot,pboot,samples +average,0.05,1.42635,0.0143222,1.39439,1.43839,1,parametric,10,1,"c(`000000001_lnorm` = 1.3915, `000000002_lnorm` = 1.42055, `000000003_lnorm` = 1.41287, `000000004_lnorm` = 1.42336, `000000005_lnorm` = 1.42911, `000000006_lnorm` = 1.40433, `000000007_lnorm` = 1.42858, `000000008_lnorm` = 1.44108, `000000009_lnorm` = 1.40699, `000000010_lnorm` = 1.4205)" diff --git a/tests/testthat/test-ggplot.R b/tests/testthat/test-ggplot.R index 64a27be29..3d26d12dc 100644 --- a/tests/testthat/test-ggplot.R +++ b/tests/testthat/test-ggplot.R @@ -109,7 +109,7 @@ test_that("plot geom_hcintersect aes", { test_that("plot geom_xribbon", { gp <- ggplot2::ggplot(boron_pred) + geom_xribbon( - ggplot2::aes(xmin = lcl, xmax = ucl, y = percent) + ggplot2::aes(xmin = lcl, xmax = ucl, y = proportion) ) expect_snapshot_plot(gp, "geom_xribbon") }) diff --git a/tests/testthat/test-hc-root.R b/tests/testthat/test-hc-root.R index 060e5a94a..a58ab5524 100644 --- a/tests/testthat/test-hc-root.R +++ b/tests/testthat/test-hc-root.R @@ -42,8 +42,8 @@ test_that("hc multi_ci all", { test_that("hc multi_ci all multiple hcs", { fits <- ssd_fit_dists(ssddata::ccme_boron) set.seed(102) - hc_average <- ssd_hc(fits, percent = c(5,10), average = TRUE, multi_ci = FALSE, multi_est = FALSE, weighted = FALSE) - hc_multi <- ssd_hc(fits, percent = c(5,10), average = TRUE, multi_ci = TRUE) + hc_average <- ssd_hc(fits, proportion = c(5,10)/100, average = TRUE, multi_ci = FALSE, multi_est = FALSE, weighted = FALSE) + hc_multi <- ssd_hc(fits, proportion = c(5,10)/100, average = TRUE, multi_ci = TRUE) expect_equal(hc_average$est, c(1.24151700389853, 2.37337471483992)) expect_equal(hc_multi$est, c(1.25677449265554, 2.38164905743083)) testthat::expect_snapshot({ @@ -54,9 +54,9 @@ test_that("hc multi_ci all multiple hcs", { test_that("hc multi_ci all multiple hcs cis", { fits <- ssd_fit_dists(ssddata::ccme_boron) set.seed(102) - hc_average <- ssd_hc(fits, percent = c(5,10), average = TRUE, multi_ci = FALSE, multi_est = FALSE, nboot = 10, ci = TRUE, weighted = FALSE) + hc_average <- ssd_hc(fits, proportion = c(5,10)/100, average = TRUE, multi_ci = FALSE, multi_est = FALSE, nboot = 10, ci = TRUE, weighted = FALSE) set.seed(105) - hc_multi <- ssd_hc(fits, percent = c(5,10), average = TRUE, multi_ci = TRUE, nboot = 10, ci = TRUE) + hc_multi <- ssd_hc(fits, proportion = c(5,10)/100, average = TRUE, multi_ci = TRUE, nboot = 10, ci = TRUE) expect_equal(hc_average$est, c(1.24151700389853, 2.37337471483992)) expect_equal(hc_multi$est, c(1.25677449265554, 2.38164905743083)) testthat::expect_snapshot({ diff --git a/tests/testthat/test-hc.R b/tests/testthat/test-hc.R index 7875c78b5..d15cb021e 100644 --- a/tests/testthat/test-hc.R +++ b/tests/testthat/test-hc.R @@ -35,9 +35,9 @@ test_that("ssd_hc list handles zero length list", { hc <- ssd_hc(structure(list(), .Names = character(0))) expect_s3_class(hc, "tbl_df") - expect_identical(colnames(hc), c("dist", "percent", "est", "se", "lcl", "ucl", "wt", "nboot", "pboot", "samples")) + expect_identical(colnames(hc), c("dist", "proportion", "est", "se", "lcl", "ucl", "wt", "nboot", "pboot", "samples")) expect_identical(hc$dist, character(0)) - expect_identical(hc$percent, numeric(0)) + expect_identical(hc$proportion, numeric(0)) expect_identical(hc$se, numeric(0)) }) @@ -45,29 +45,29 @@ test_that("ssd_hc list works null values handles zero length list", { hc <- ssd_hc(list("lnorm" = NULL)) expect_s3_class(hc, "tbl_df") - expect_identical(colnames(hc), c("dist", "percent", "est", "se", "lcl", "ucl", "wt", "nboot", "pboot")) + expect_identical(colnames(hc), c("dist", "proportion", "est", "se", "lcl", "ucl", "wt", "nboot", "pboot")) expect_equal(hc$dist, "lnorm") - expect_identical(hc$percent, 5) + expect_identical(hc$proportion, 0.05) expect_equal(hc$est, 0.193040816698737) expect_equal(hc$se, NA_real_) }) test_that("ssd_hc list works multiple percent values", { - hc <- ssd_hc(list("lnorm" = NULL), percent = c(1, 99)) + hc <- ssd_hc(list("lnorm" = NULL), proportion = c(1, 99)/100) expect_s3_class(hc, "tbl_df") - expect_identical(colnames(hc), c("dist", "percent", "est", "se", "lcl", "ucl", "wt", "nboot", "pboot")) - expect_identical(hc$percent, c(1, 99)) + expect_identical(colnames(hc), c("dist", "proportion", "est", "se", "lcl", "ucl", "wt", "nboot", "pboot")) + expect_identical(hc$proportion, c(1, 99)/100) expect_equal(hc$dist, c("lnorm", "lnorm")) expect_equal(hc$est, c(0.097651733070336, 10.2404736563121)) expect_identical(hc$se, c(NA_real_, NA_real_)) }) test_that("ssd_hc list works partial percent values", { - hc <- ssd_hc(list("lnorm" = NULL), percent = c(50.5)) + hc <- ssd_hc(list("lnorm" = NULL), proportion = c(50.5)/100) expect_s3_class(hc, "tbl_df") - expect_identical(colnames(hc), c("dist", "percent", "est", "se", "lcl", "ucl", "wt", "nboot", "pboot")) - expect_identical(hc$percent, 50.5) + expect_identical(colnames(hc), c("dist", "proportion", "est", "se", "lcl", "ucl", "wt", "nboot", "pboot")) + expect_identical(hc$proportion, 50.5/100) expect_equal(hc$dist, "lnorm") expect_equal(hc$est, 1.01261234261044) expect_identical(hc$se, NA_real_) @@ -76,9 +76,8 @@ test_that("ssd_hc list works partial percent values", { test_that("ssd_hc list works specified values", { hc <- ssd_hc(list("lnorm" = list(meanlog = 2, sdlog = 2))) expect_s3_class(hc, "tbl_df") - expect_identical(colnames(hc), c("dist", "percent", "est", "se", "lcl", "ucl", "wt", "nboot", "pboot")) - expect_identical(hc$percent, 5) - expect_true(vld_whole_numeric(hc$percent)) + expect_identical(colnames(hc), c("dist", "proportion", "est", "se", "lcl", "ucl", "wt", "nboot", "pboot")) + expect_identical(hc$proportion, 0.05) expect_equal(hc$dist, "lnorm") expect_equal(hc$est, 0.275351379333677) expect_equal(hc$se, NA_real_) @@ -88,8 +87,8 @@ test_that("ssd_hc list works multiple NULL distributions", { hc <- ssd_hc(list("lnorm" = NULL, "llogis" = NULL)) expect_s3_class(hc, "tbl_df") - expect_identical(colnames(hc), c("dist", "percent", "est", "se", "lcl", "ucl", "wt", "nboot", "pboot")) - expect_identical(hc$percent, c(5, 5)) + expect_identical(colnames(hc), c("dist", "proportion", "est", "se", "lcl", "ucl", "wt", "nboot", "pboot")) + expect_identical(hc$proportion, c(5, 5)/100) expect_equal(hc$dist, c("lnorm", "llogis")) expect_equal(hc$est, c(0.193040816698737, 0.0526315789473684)) expect_equal(hc$se, c(NA_real_, NA_real_)) @@ -97,11 +96,11 @@ test_that("ssd_hc list works multiple NULL distributions", { test_that("ssd_hc list works multiple NULL distributions with multiple percent", { - hc <- ssd_hc(list("lnorm" = NULL, "llogis" = NULL), percent = c(1, 99)) + hc <- ssd_hc(list("lnorm" = NULL, "llogis" = NULL), proportion = c(1, 99)/100) expect_s3_class(hc, "tbl_df") - expect_identical(colnames(hc), c("dist", "percent", "est", "se", "lcl", "ucl", "wt", "nboot", "pboot")) + expect_identical(colnames(hc), c("dist", "proportion", "est", "se", "lcl", "ucl", "wt", "nboot", "pboot")) expect_equal(hc$dist, c("lnorm", "lnorm", "llogis", "llogis")) - expect_identical(hc$percent, c(1, 99, 1, 99)) + expect_identical(hc$proportion, c(1, 99, 1, 99)/100) expect_equal(hc$est, c(0.097651733070336, 10.2404736563121, 0.0101010101010101, 98.9999999999999)) expect_equal(hc$se, c(NA_real_, NA_real_, NA_real_, NA_real_)) }) @@ -110,11 +109,11 @@ test_that("ssd_hc fitdists works zero length percent", { fits <- ssd_fit_dists(ssddata::ccme_boron, dists = "lnorm") - hc <- ssd_hc(fits, numeric(0)) + hc <- ssd_hc(fits, proportion = numeric(0)) expect_s3_class(hc, class = "tbl_df") - expect_identical(colnames(hc), c("dist", "percent", "est", "se", "lcl", "ucl", "wt", "nboot", "pboot", "samples")) + expect_identical(colnames(hc), c("dist", "proportion", "est", "se", "lcl", "ucl", "wt", "nboot", "pboot", "samples")) expect_equal(hc$dist, character(0)) - expect_identical(hc$percent, numeric(0)) + expect_identical(hc$proportion, numeric(0)) expect_equal(hc$est, numeric(0)) expect_equal(hc$se, numeric(0)) }) @@ -123,7 +122,7 @@ test_that("ssd_hc fitdists works NA percent", { fits <- ssd_fit_dists(ssddata::ccme_boron, dists = "lnorm") - hc <- ssd_hc(fits, NA_real_) + hc <- ssd_hc(fits, proportion = NA_real_) expect_s3_class(hc, "tbl_df") expect_snapshot_data(hc, "hc114") }) @@ -132,7 +131,7 @@ test_that("ssd_hc fitdists works 0 percent", { fits <- ssd_fit_dists(ssddata::ccme_boron, dists = "lnorm") - hc <- ssd_hc(fits, 0) + hc <- ssd_hc(fits, proportion = 0) expect_s3_class(hc, "tbl_df") expect_snapshot_data(hc, "hc122") }) @@ -141,7 +140,7 @@ test_that("ssd_hc fitdists works 100 percent", { fits <- ssd_fit_dists(ssddata::ccme_boron, dists = "lnorm") - hc <- ssd_hc(fits, 100) + hc <- ssd_hc(fits, proportion = 1) expect_s3_class(hc, "tbl_df") expect_snapshot_data(hc, "hc130") }) @@ -150,7 +149,7 @@ test_that("ssd_hc fitdists works multiple percents", { fits <- ssd_fit_dists(ssddata::ccme_boron, dists = "lnorm") - hc <- ssd_hc(fits, percent = c(1, 99)) + hc <- ssd_hc(fits, proportion = c(1, 99)/100) expect_s3_class(hc, "tbl_df") expect_snapshot_data(hc, "hc138") }) @@ -159,7 +158,7 @@ test_that("ssd_hc fitdists works fractions", { fits <- ssd_fit_dists(ssddata::ccme_boron, dists = "lnorm") - hc <- ssd_hc(fits, percent = 50.5) + hc <- ssd_hc(fits, proportion = 50.5/100) expect_s3_class(hc, "tbl_df") expect_snapshot_data(hc, "hc505") }) @@ -189,7 +188,7 @@ test_that("ssd_hc fitdists averages single dist by multiple percent", { fits <- ssd_fit_dists(ssddata::ccme_boron, dists = "lnorm") - hc <- ssd_hc(fits, average = TRUE, percent = 1:99) + hc <- ssd_hc(fits, average = TRUE, proportion = 1:99/100) expect_s3_class(hc, "tbl_df") expect_snapshot_data(hc, "hc153") }) @@ -198,7 +197,7 @@ test_that("ssd_hc fitdists not average single dist by multiple percent gives who fits <- ssd_fit_dists(ssddata::ccme_boron, dists = "lnorm") - hc <- ssd_hc(fits, average = FALSE, percent = 1:99) + hc <- ssd_hc(fits, average = FALSE, proportion = 1:99/100) expect_s3_class(hc, "tbl_df") expect_snapshot_data(hc, "hc161") }) @@ -623,11 +622,11 @@ test_that("ssd_hc multiple values", { fits <- ssd_fit_dists(ssddata::ccme_boron, dist = c("lnorm", "lgumbel")) set.seed(102) - hc_unfix <- ssd_hc(fits, percent = c(5,10), nboot = 100, ci = TRUE, weighted = FALSE, samples = TRUE) + hc_unfix <- ssd_hc(fits, proportion = c(5, 10) / 100, nboot = 100, ci = TRUE, weighted = FALSE, samples = TRUE) expect_snapshot_data(hc_unfix, "hc_unfixmulti") set.seed(102) - hc_fix <- ssd_hc(fits, percent = c(5,10), nboot = 100, ci = TRUE, weighted = TRUE, samples = TRUE) + hc_fix <- ssd_hc(fits, proportion = c(5, 10) / 100, nboot = 100, ci = TRUE, weighted = TRUE, samples = TRUE) expect_snapshot_data(hc_fix, "hc_fixmulti") }) @@ -637,7 +636,7 @@ test_that("ssd_hc multiple values save_to", { fits <- ssd_fit_dists(ssddata::ccme_boron, dist = c("lnorm", "lgumbel")) set.seed(102) - hc <- ssd_hc(fits, percent = c(5,10), nboot = 2, save_to = dir, ci = TRUE) + hc <- ssd_hc(fits, proportion = c(5, 10) / 100, nboot = 2, save_to = dir, ci = TRUE) expect_identical(list.files(dir), c("data_000000000_multi.csv", "data_000000001_multi.csv", "data_000000002_multi.csv", "estimates_000000000_multi.rds", "estimates_000000001_multi.rds", "estimates_000000002_multi.rds")) @@ -727,3 +726,22 @@ test_that("hc weighted bootie", { expect_snapshot_boot_data(hc_weighted2, "hc_weighted2") expect_snapshot_boot_data(hc_unweighted2, "hc_unweighted2") }) + +test_that("hc percent deprecated", { + + fits <- ssd_fit_dists(ssddata::ccme_boron) + lifecycle::expect_deprecated(hc <- ssd_hc(fits, percent = 10)) + hc2 <- ssd_hc(fits, proportion = 0.1) + expect_identical(hc2, hc) + + lifecycle::expect_deprecated(hc <- ssd_hc(fits, percent = c(5, 10))) + hc2 <- ssd_hc(fits, proportion = c(0.05, 0.1)) + expect_identical(hc2, hc) +}) + +test_that("hc proportion multiple decimal places", { + + fits <- ssd_fit_dists(ssddata::ccme_boron) + hc2 <- ssd_hc(fits, proportion = 0.111111) + expect_identical(hc2$proportion, 0.111111) +}) diff --git a/tests/testthat/test-hcp-root.R b/tests/testthat/test-hcp-root.R index f8dfb1e25..4c78d3de3 100644 --- a/tests/testthat/test-hcp-root.R +++ b/tests/testthat/test-hcp-root.R @@ -17,11 +17,11 @@ test_that("hp is hc conc = 1 multi_ci = TRUE", { fits <- ssd_fit_dists(ssddata::ccme_boron) conc <- 1 hp_multi <- ssd_hp(fits, conc = conc, average = TRUE, multi_ci = TRUE) - hc_multi <- ssd_hc(fits, percent = hp_multi$est, average = TRUE, multi_ci = TRUE) + hc_multi <- ssd_hc(fits, proportion = hp_multi$est/100, average = TRUE, multi_ci = TRUE) expect_equal(hc_multi$est, 1) for(i in 1:10) { hp_multi <- ssd_hp(fits, conc = hc_multi$est, average = TRUE, multi_ci = TRUE) - hc_multi <- ssd_hc(fits, percent = hp_multi$est, average = TRUE, multi_ci = TRUE) + hc_multi <- ssd_hc(fits, proportion = hp_multi$est/100, average = TRUE, multi_ci = TRUE) } expect_equal(hc_multi$est, 1) }) @@ -30,11 +30,11 @@ test_that("hp is hc conc = 10 multi_ci = TRUE", { fits <- ssd_fit_dists(ssddata::ccme_boron) conc <- 10 hp_multi <- ssd_hp(fits, conc = conc, average = TRUE, multi_ci = TRUE) - hc_multi <- ssd_hc(fits, percent = hp_multi$est, average = TRUE, multi_ci = TRUE) + hc_multi <- ssd_hc(fits, proportion = hp_multi$est/100, average = TRUE, multi_ci = TRUE) expect_equal(hc_multi$est, 10.00000012176) for(i in 1:10) { hp_multi <- ssd_hp(fits, conc = hc_multi$est, average = TRUE, multi_ci = TRUE) - hc_multi <- ssd_hc(fits, percent = hp_multi$est, average = TRUE, multi_ci = TRUE) + hc_multi <- ssd_hc(fits, proportion = hp_multi$est/100, average = TRUE, multi_ci = TRUE) } expect_equal(hc_multi$est, 10) }) diff --git a/tests/testthat/test-hp.R b/tests/testthat/test-hp.R index 3560d3ec1..14935ca8c 100644 --- a/tests/testthat/test-hp.R +++ b/tests/testthat/test-hp.R @@ -135,13 +135,13 @@ test_that("hp fitdists gives different answer with model averaging as hc not sam data <- ssddata::aims_molybdenum_marine fits_lgumbel <- ssd_fit_dists(data, dists = "lgumbel") - expect_equal(ssd_hp(fits_lgumbel, ssd_hc(fits_lgumbel, percent = 5)$est)$est, 5) + expect_equal(ssd_hp(fits_lgumbel, ssd_hc(fits_lgumbel, proportion = 5/100)$est)$est, 5) fits_lnorm_lnorm <- ssd_fit_dists(data, dists = "lnorm_lnorm") - expect_equal(ssd_hp(fits_lnorm_lnorm, ssd_hc(fits_lnorm_lnorm, percent = 5)$est)$est, 5) + expect_equal(ssd_hp(fits_lnorm_lnorm, ssd_hc(fits_lnorm_lnorm, proportion = 5/100)$est)$est, 5) fits_both <- ssd_fit_dists(data, dists = c("lgumbel", "lnorm_lnorm")) - expect_equal(ssd_hp(fits_both, ssd_hc(fits_both, percent = 5, multi_ci = FALSE, multi_est = FALSE, weighted = FALSE)$est)$est, 4.59188450624579) + expect_equal(ssd_hp(fits_both, ssd_hc(fits_both, proportion = 5/100, multi_ci = FALSE, multi_est = FALSE, weighted = FALSE)$est)$est, 4.59188450624579) }) test_that("ssd_hp fitdists correct for rescaling", { diff --git a/tests/testthat/test-zzz-unstable.R b/tests/testthat/test-zzz-unstable.R index a28068bc6..9afe9b1f3 100644 --- a/tests/testthat/test-zzz-unstable.R +++ b/tests/testthat/test-zzz-unstable.R @@ -263,7 +263,7 @@ test_that("plot geoms", { geom_ssdsegment(data = ssddata::ccme_boron, ggplot2::aes(x = Conc, xend = Conc * 2)) + geom_hcintersect(xintercept = 100, yintercept = 0.5) + geom_xribbon( - ggplot2::aes(xmin = lcl, xmax = ucl, y = percent / 100), + ggplot2::aes(xmin = lcl, xmax = ucl, y = proportion), alpha = 1 / 3 ) expect_snapshot_plot(gp, "geoms_all") diff --git a/vignettes/faqs.Rmd b/vignettes/faqs.Rmd index 864b01c76..e86fde108 100644 --- a/vignettes/faqs.Rmd +++ b/vignettes/faqs.Rmd @@ -28,7 +28,7 @@ dist <- ssdtools::ssd_fit_dists(ssddata::ccme_boron) pred <- predict(dist, ci = FALSE) ssdtools::ssd_plot_cdf(dist) + - geom_line(data = pred, aes(x = est, y = percent / 100)) + geom_line(data = pred, aes(x = est, y = proportion)) ``` ## How do I fit distributions to multiple groups such taxa and/or chemicals? diff --git a/vignettes/ssdtools.Rmd b/vignettes/ssdtools.Rmd index 5c556addb..c07c9b69c 100644 --- a/vignettes/ssdtools.Rmd +++ b/vignettes/ssdtools.Rmd @@ -212,20 +212,20 @@ ggplot(ccme_boron) + The third is `geom_xribbon()` which plots species sensitivity confidence intervals ```{r} ggplot(boron_pred) + - geom_xribbon(aes(xmin = lcl, xmax = ucl, y = percent / 100)) + geom_xribbon(aes(xmin = lcl, xmax = ucl, y = proportion)) ``` And the fourth is `geom_hcintersect()` which plots hazard concentrations ```{r} ggplot() + - geom_hcintersect(xintercept = c(1, 2, 3), yintercept = c(5, 10, 20) / 100) + geom_hcintersect(xintercept = c(1, 2, 3), yintercept = c(0.05, 0.1, 0.2)) ``` They can be combined together as follows ```{r} gp <- ggplot(boron_pred, aes(x = est)) + - geom_xribbon(aes(xmin = lcl, xmax = ucl, y = percent / 100), alpha = 0.2) + - geom_line(aes(y = percent / 100)) + + geom_xribbon(aes(xmin = lcl, xmax = ucl, y = proportion), alpha = 0.2) + + geom_line(aes(y = proportion)) + geom_ssdsegment(data = ccme_boron, aes(x = Conc / 2, xend = Conc * 2)) + geom_ssdpoint(data = ccme_boron, aes(x = Conc / 2)) + geom_ssdpoint(data = ccme_boron, aes(x = Conc * 2)) + @@ -242,7 +242,7 @@ gp <- gp + coord_trans(x = "log10") + breaks = scales::trans_breaks("log10", function(x) 10^x), labels = comma_signif ) -print(gp + geom_hcintersect(xintercept = boron_hc5$est, yintercept = 5 / 100)) +print(gp + geom_hcintersect(xintercept = boron_hc5$est, yintercept = 0.05)) ``` The most recent plot can be saved as a file using `ggsave()`, which also allows the user to set the resolution.