From c720a433c1fedc854ccc5716ab8bdce67e836043 Mon Sep 17 00:00:00 2001 From: jgabry Date: Thu, 28 Mar 2024 15:31:31 -0600 Subject: [PATCH] Update rstanarm.Rmd --- vignettes/rstanarm.Rmd | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/vignettes/rstanarm.Rmd b/vignettes/rstanarm.Rmd index 5d136510..700c88b7 100644 --- a/vignettes/rstanarm.Rmd +++ b/vignettes/rstanarm.Rmd @@ -342,8 +342,11 @@ of 1000 iterations that is discarded). All chains must converge to the target distribution for inferences to be valid. For most models, the default settings are sufficient, but if you see a warning message about Markov chains not converging, the first thing to try is increasing the number of iterations. This -can be done by specifying the `iter` argument (e.g. `iter = 3000`). However, if all parameters have proper priors (no priors were set to `NULL`), and you used the default values -for iterations (2000) and chains (4), and Rhats (explained below) are greater than 2, then increasing the number of iterations alone is unlikely to solve to the problem. +can be done by specifying the `iter` argument. However, if all parameters have +proper priors (no priors were set to `NULL`), and you used the default values +for iterations (2000) and chains (4), and Rhats (explained below) are greater +than 2, then increasing the number of iterations alone is unlikely to solve to +the problem. One way to monitor whether a chain has converged to the equilibrium distribution is to compare its behavior to other randomly initialized chains. This is the