Package: bayesMeanScale 0.1.4

bayesMeanScale: 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.

Authors:David M. Dalenberg [aut, cre]

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bayesMeanScale.pdf |bayesMeanScale.html✨
bayesMeanScale/json (API)
NEWS

# Install 'bayesMeanScale' in R:
install.packages('bayesMeanScale', repos = c('https://dalenbe2.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/dalenbe2/bayesmeanscale/issues

On CRAN:

4.74 score 1 scripts 674 downloads 5 exports 24 dependencies

Last updated 5 months agofrom:0778dfc3d8. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 23 2024
R-4.5-winOKNov 23 2024
R-4.5-linuxOKNov 23 2024
R-4.4-winOKNov 23 2024
R-4.4-macOKNov 23 2024
R-4.3-winNOTENov 23 2024
R-4.3-macNOTENov 23 2024

Exports:bayesCountMargEffFbayesCountPredsFbayesMargCompareFbayesMargEffFbayesPredsF

Dependencies:abindbackportsbayestestRcheckmateclidata.tabledatawizarddistributionalfansigenericsglueinsightlifecyclemagrittrmatrixStatsnumDerivpillarpkgconfigposteriorrlangtensorAtibbleutf8vctrs

Introduction to 'bayesMeanScale'

Rendered fromintroduction.Rmdusingknitr::rmarkdownon Nov 23 2024.

Last update: 2024-05-30
Started: 2024-04-03