From 7790447e1e1f74dec986b92ed0c8b4dfac6ea065 Mon Sep 17 00:00:00 2001 From: Joe Thorley Date: Tue, 9 Jan 2024 00:43:21 -0600 Subject: [PATCH] Bump version to 1.0.6.9009 --- DESCRIPTION | 2 +- NEWS.md | 32 +++++++++++++++++++------------- 2 files changed, 20 insertions(+), 14 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index fd872077b..576c2c3a4 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: ssdtools Title: Species Sensitivity Distributions -Version: 1.0.6.9008 +Version: 1.0.6.9009 Authors@R: c( person("Joe", "Thorley", , "joe@poissonconsulting.ca", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7683-4592")), diff --git a/NEWS.md b/NEWS.md index 9c8178a9e..34a0a88e1 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,26 +1,32 @@ -# ssdtools 1.0.6.9008 +# ssdtools 1.0.6.9009 Additions -- `ssd_hc.fitdists()` and `ssd_hp.fitdists()` now have `multi = TRUE` -argument to get estimates based on `ssd_qmulti()` and `ssd_pmulti()` when -`average = TRUE`. -- Added `ssd_pmulti()`, `ssd_qmulti()` and `ssd_rmulti()` -for weights and parameter estimates for combined distributions. -- Implemented bootstrapping for `ssd_hc.fitdists()` and `ssd_hp.fitdists()` based on combined distributions. -- Add `fix_weights = TRUE` argument to `ssd_hc()` and `ssd_hp()` to specify whether to fix the model weights when performing `multi` bootstrapping. -- Added `save_to` argument to specify a directory in which to save the bootstrap datasets as csv files and estimates as rds files. The files are named `data_000000001_xx.csv`, `estimates_000000001_xx.rds` etc where `xx` is the distribution. The parent data set and estimates are named `boot_000000000_xx.csv` and `estimates_000000000_xx.csv`. -- Added `ssd_hp.fitburrlioz()` function. -- Added `ssd_exx()` functions to get -default parameter estimates for distributions. - Added David Fox and Rebecca Fisher as co-authors. +- Added to `ssd_hc()` and `ssd_hp()` + - `multi_est = TRUE` argument to calculate model averaged estimates + treating the distributions as constituting a single mixture distribution. + - `multi_ci = TRUE` argument to calculate model averaged confidence intervals + treating the distributions as constituting a single mixture distribution. + - `weighted = TRUE` argument to specify whether to use the original model weights versus + re-estimating for each bootstrap sample unless `multi_ci = FALSE` in which case it + specifies whether to take bootstrap samples from each distribution proportional to + its weight versus calculating the weighted arithmetic means of the lower + and upper confidence limits for each distribution. + - `samples` argument to include bootstrap samples as list of numeric vector(s). + - `save_to` argument to specify a directory in which to save the bootstrap datasets as csv files and parameter estimates as rds files. The files are named `data_000000001_xx.csv` and `estimates_000000001_xx.rds` etc where `xx` is the distribution. The parent data set and estimates are named `boot_000000000_xx.csv` and `estimates_000000000_xx.csv`. +- Added `ssd_pmulti()`, `ssd_qmulti()` and `ssd_rmulti()` for combined mixture distributions. +- Added `ssd_exx()` functions to get default parameter estimates for distributions. +- Added `ssd_hp.fitburrlioz()` function to get hazard proportion. Modifications -- `estimates.fitdists()` now returns all distributions by default and includes weights as parameters. +- `estimates.fitdists()` now includes weights in returned parameters as well as an +`all_estimates = FALSE` argument to allow parameter values for all implemented distributions to be included. - `ssd_fit_bcanz()`, `ssd_wqg_bc()` and `ssd_wqg_burrlioz()` no longer rescale data by default. +- `rescale = TRUE` now divides by the geometric mean of the minimum and maximum positive finite values as opposed to dividing by the geometric mean of the maximum finite value. - seeds now allocated to bootstrap samples as opposed to distributions (this results in a speed gain when more cores than the number of distributions). Fixes