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bayesMeanScale  

Bayesian Post-Estimation on the Mean Scale
View on CRAN: Click here


Download and install bayesMeanScale package within the R console
Install from CRAN:
install.packages("bayesMeanScale")

Install from Github:
library("remotes")
install_github("cran/bayesMeanScale")

Install by package version:
library("remotes")
install_version("bayesMeanScale", "0.1.4")



Attach the package and use:
library("bayesMeanScale")
Maintained by
David M. Dalenberg
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-04-23
Latest Update: 2024-04-27
Description:
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.
How to cite:
David M. Dalenberg (2024). bayesMeanScale: Bayesian Post-Estimation on the Mean Scale. R package version 0.1.4, https://cran.r-project.org/web/packages/bayesMeanScale. Accessed 07 Nov. 2024.
Previous versions and publish date:
0.1.0 (2024-04-23 13:30), 0.1.1 (2024-04-28 01:00), 0.1.2 (2024-05-18 14:30), 0.1.3 (2024-05-23 16:30)
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Complete documentation for bayesMeanScale
Functions, R codes and Examples using the bayesMeanScale R package
Full bayesMeanScale package functions and examples
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