From d5f847dd723cb89c4e5d62664fae73f7d3358e43 Mon Sep 17 00:00:00 2001 From: Sam Date: Tue, 11 Jun 2024 19:47:24 +0100 Subject: [PATCH] correct type specification --- .../ObservationErrorModels/NegativeBinomialError.jl | 2 +- .../src/EpiObsModels/ObservationErrorModels/PoissonError.jl | 2 +- EpiAware/src/EpiObsModels/ObservationErrorModels/methods.jl | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/EpiAware/src/EpiObsModels/ObservationErrorModels/NegativeBinomialError.jl b/EpiAware/src/EpiObsModels/ObservationErrorModels/NegativeBinomialError.jl index 26778ddad..98aad3fb5 100644 --- a/EpiAware/src/EpiObsModels/ObservationErrorModels/NegativeBinomialError.jl +++ b/EpiAware/src/EpiObsModels/ObservationErrorModels/NegativeBinomialError.jl @@ -14,7 +14,7 @@ nb_model = generate_observations(nb, missing, fill(10, 10)) rand(nb_model) ``` " -@kwdef struct NegativeBinomialError{S <: Sampleable, T <: AbstractFloat} <: +@kwdef struct NegativeBinomialError{S <: Sampleable} <: AbstractTuringObservationErrorModel "The prior distribution for the cluster factor." cluster_factor_prior::S = HalfNormal(0.01) diff --git a/EpiAware/src/EpiObsModels/ObservationErrorModels/PoissonError.jl b/EpiAware/src/EpiObsModels/ObservationErrorModels/PoissonError.jl index 1424c7a60..491cf13de 100644 --- a/EpiAware/src/EpiObsModels/ObservationErrorModels/PoissonError.jl +++ b/EpiAware/src/EpiObsModels/ObservationErrorModels/PoissonError.jl @@ -13,7 +13,7 @@ poi_model = generate_observations(poi, missing, fill(10, 10)) rand(poi_model) ``` " -struct PoissonError{T <: AbstractFloat} <: AbstractTuringObservationErrorModel +struct PoissonError <: AbstractTuringObservationErrorModel end @doc raw" diff --git a/EpiAware/src/EpiObsModels/ObservationErrorModels/methods.jl b/EpiAware/src/EpiObsModels/ObservationErrorModels/methods.jl index 2bbab14fa..342f90d7d 100644 --- a/EpiAware/src/EpiObsModels/ObservationErrorModels/methods.jl +++ b/EpiAware/src/EpiObsModels/ObservationErrorModels/methods.jl @@ -15,7 +15,7 @@ It dispatches to the `observation_error` function to generate the observation er @assert length(y_t)==length(Y_t) "The observation vector and expected observation vector must have the same length." end - pad_Y_t = Y_t + 1e-6 + pad_Y_t = Y_t .+ 1e-6 for i in findfirst(!ismissing, Y_t):length(Y_t) y_t[i] ~ observation_error(obs_model, pad_Y_t[i], priors...)