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 630 downloads 5 exports 24 dependencies

Last updated 4 months agofrom:0778dfc3d8. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 24 2024
R-4.5-winOKOct 24 2024
R-4.5-linuxOKOct 24 2024
R-4.4-winOKOct 24 2024
R-4.4-macOKOct 24 2024
R-4.3-winNOTEOct 24 2024
R-4.3-macNOTEOct 24 2024

Exports:bayesCountMargEffFbayesCountPredsFbayesMargCompareFbayesMargEffFbayesPredsF

Dependencies:abindbackportsbayestestRcheckmateclidata.tabledatawizarddistributionalfansigenericsglueinsightlifecyclemagrittrmatrixStatsnumDerivpillarpkgconfigposteriorrlangtensorAtibbleutf8vctrs

Introduction to 'bayesMeanScale'

Rendered fromintroduction.Rmdusingknitr::rmarkdownon Oct 24 2024.

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