Bayesian Post-Estimation on the Mean Scale

Computes Bayesian posterior distributions of predictions, marginal effects, and differences of marginal effects for various generalized linear models. Importantly, the posteriors are on the mean (response) scale, allowing for more natural interpretation than summaries on the link scale. Also, predictions and marginal effects of the count probabilities for Poisson and negative binomial models can be computed.


bayesMeanScale

CRAN_Status_Badge

bayesMeanScale is an R package designed to compute Bayesian posterior distributions of predictions, marginal effects, and differences of marginal effects.

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("bayesMeanScale")

0.2.2 by David M. Dalenberg, 7 months ago


https://github.com/dalenbe2/bayesMeanScale


Report a bug at https://github.com/dalenbe2/bayesMeanScale/issues


Browse source code at https://github.com/cran/bayesMeanScale


Authors: David M. Dalenberg [aut, cre]


Documentation:   PDF Manual  


GPL (>= 3) license


Imports bayestestR, data.table, magrittr, posterior

Suggests flextable, knitr, MASS, rmarkdown, rstanarm, testthat


See at CRAN