From fcc9d218737473ae9f42b9e449ce648d42fd6952 Mon Sep 17 00:00:00 2001 From: Jose Storopoli Date: Mon, 23 Jan 2023 11:11:13 -0300 Subject: [PATCH] fix Exponential priors (#74) --- _literate/11_multilevel_models.jl | 6 +++--- _literate/12_Turing_tricks.jl | 4 ++-- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/_literate/11_multilevel_models.jl b/_literate/11_multilevel_models.jl index 3e1b2007..b4a59409 100644 --- a/_literate/11_multilevel_models.jl +++ b/_literate/11_multilevel_models.jl @@ -102,7 +102,7 @@ setprogress!(false) # hide #priors α ~ Normal(mean(y), 2.5 * std(y)) # population-level intercept β ~ filldist(Normal(0, 2), predictors) # population-level coefficients - σ ~ Exponential(1 / std(y)) # residual SD + σ ~ Exponential(std(y)) # residual SD #prior for variance of random intercepts #usually requires thoughtful specification τ ~ truncated(Cauchy(0, 2); lower=0) # group-level SDs intercepts @@ -141,7 +141,7 @@ end; @model function varying_slope(X, idx, y; n_gr=length(unique(idx)), predictors=size(X, 2)) #priors α ~ Normal(mean(y), 2.5 * std(y)) # population-level intercept - σ ~ Exponential(1 / std(y)) # residual SD + σ ~ Exponential(std(y)) # residual SD #prior for variance of random slopes #usually requires thoughtful specification τ ~ filldist(truncated(Cauchy(0, 2); lower=0), n_gr) # group-level slopes SDs @@ -183,7 +183,7 @@ end; ) #priors α ~ Normal(mean(y), 2.5 * std(y)) # population-level intercept - σ ~ Exponential(1 / std(y)) # residual SD + σ ~ Exponential(std(y)) # residual SD #prior for variance of random intercepts and slopes #usually requires thoughtful specification τₐ ~ truncated(Cauchy(0, 2); lower=0) # group-level SDs intercepts diff --git a/_literate/12_Turing_tricks.jl b/_literate/12_Turing_tricks.jl index 2e4bdb37..a4095ab0 100644 --- a/_literate/12_Turing_tricks.jl +++ b/_literate/12_Turing_tricks.jl @@ -193,7 +193,7 @@ chain_ncp_funnel = sample(ncp_funnel(), NUTS(), MCMCThreads(), 1_000, 4) #priors α ~ Normal(mean(y), 2.5 * std(y)) # population-level intercept β ~ filldist(Normal(0, 2), predictors) # population-level coefficients - σ ~ Exponential(1 / std(y)) # residual SD + σ ~ Exponential(std(y)) # residual SD #prior for variance of random intercepts #usually requires thoughtful specification τ ~ truncated(Cauchy(0, 2); lower=0) # group-level SDs intercepts @@ -212,7 +212,7 @@ end; #priors α ~ Normal(mean(y), 2.5 * std(y)) # population-level intercept β ~ filldist(Normal(0, 2), predictors) # population-level coefficients - σ ~ Exponential(1 / std(y)) # residual SD + σ ~ Exponential(std(y)) # residual SD #prior for variance of random intercepts #usually requires thoughtful specification