@Xinyi_Chen , @andrewgelman and I are working on updating the MI package from a backend of bayesglm to a backend of rstanarm with the “optimize” setting. Are there any diagnostics that we ought to be looking at?

@avehtari added a few to 2.19 [image] New releases of rstanarm and rstantools R packages Announcements Pareto diagnostic and Pareto smoothed importance sampling https://arxiv.org/abs/1507.02646 is used to diagnose and improve inference when using stan_glm with algorithm=‘o…

My main recommendation is that we should be using much stronger default priors. Perhaps something like Cauchy(0, 0.5) for all coefs except for the constant term?

Rstanarm(optimize = TRUE) diagnostics

Interfaces rstanarm

bgoodri November 14, 2019, 11:03pm 2

@avehtari added a few to 2.19

Topic		Replies	Views
New diagnostics for stan_glm and algorithm='optimizing' rstanarm	1	752	March 14, 2019
New releases of rstanarm and rstantools R packages Announcements	12	1385	October 12, 2019
Maximum likelihood via rstanarm::stan_glm rstanarm	1	583	December 2, 2022
What is stan_glm(algorithm = "optimizing") doing? rstanarm	1	606	September 7, 2020
Optimization rules General	3	683	April 5, 2019

Rstanarm(optimize = TRUE) diagnostics

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