CRAN/E | posterior

posterior

Tools for Working with Posterior Distributions

Installation

About

Provides useful tools for both users and developers of packages for fitting Bayesian models or working with output from Bayesian models. The primary goals of the package are to: (a) Efficiently convert between many different useful formats of draws (samples) from posterior or prior distributions. (b) Provide consistent methods for operations commonly performed on draws, for example, subsetting, binding, or mutating draws. (c) Provide various summaries of draws in convenient formats. (d) Provide lightweight implementations of state of the art posterior inference diagnostics. References: Vehtari et al. (2021) doi:10.1214/20-BA1221.

Citation posterior citation info
mc-stan.org/posterior/
discourse.mc-stan.org/
Bug report File report

Key Metrics

Version 1.5.0
R ≥ 3.2.0
Published 2023-10-31 149 days ago
Needs compilation? no
License BSD_3_clause
License File
CRAN checks posterior results

Downloads

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Maintainer

Maintainer

Paul-Christian Bürkner

paul.buerkner@gmail.com

Authors

Paul-Christian Bürkner

aut / cre

Jonah Gabry

aut

Matthew Kay

aut

Aki Vehtari

aut

Måns Magnusson

ctb

Rok Češnovar

ctb

Ben Lambert

ctb

Ozan Adıgüzel

ctb

Jacob Socolar

ctb

Material

README
NEWS
Reference manual
Package source

Vignettes

The posterior R package
rvar: The Random Variable Datatype

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

posterior archive

Depends

R ≥ 3.2.0

Imports

methods
abind
checkmate
rlang ≥ 1.0.6
stats
tibble ≥3.1.0
vctrs ≥ 0.5.0
tensorA
pillar
distributional
parallel
matrixStats

Suggests

testthat ≥ 2.1.0
caret ≥ 6.0.84
gbm ≥ 2.1.8
randomForest ≥ 4.6.14
e1071 ≥ 1.7.3
dplyr
tidyr
knitr
ggplot2
ggdist
rmarkdown

Reverse Imports

BASiCS
BayesMultiMode
bayesplot
brms
brms.mmrm
brmsmargins
bssm
DSSP
dynamite
historicalborrow
jagstargets
measr
OncoBayes2
reslr
rstanarm
tidybayes
voi

Reverse Suggests

bayestestR
bennu
chkptstanr
easycensus
ggdist
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marginaleffects
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parameters
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