fix Exponential priors (#74)

storopoli · Jan 23, 2023 · fcc9d21 · fcc9d21
1 parent ffa581d
commit fcc9d21
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Showing 2 changed files with 5 additions and 5 deletions.
diff --git 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
@@ -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