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bayesplot (version 1.8.0)

Plotting for Bayesian Models

Description

Plotting functions for posterior analysis, MCMC diagnostics, prior and posterior predictive checks, and other visualizations to support the applied Bayesian workflow advocated in Gabry, Simpson, Vehtari, Betancourt, and Gelman (2019) . The package is designed not only to provide convenient functionality for users, but also a common set of functions that can be easily used by developers working on a variety of R packages for Bayesian modeling, particularly (but not exclusively) packages interfacing with 'Stan'.

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Version

Install

install.packages('bayesplot')

Monthly Downloads

41,522

Version

1.8.0

License

GPL (>= 3)

Maintainer

Jonah Gabry

Last Published

January 10th, 2021

Functions in bayesplot (1.8.0)

MCMC-intervals

Plot interval estimates from MCMC draws
MCMC-overview

Plots for Markov chain Monte Carlo simulations
MCMC-distributions

Histograms and kernel density plots of MCMC draws
MCMC-nuts

Diagnostic plots for the No-U-Turn-Sampler (NUTS)
MCMC-combos

Combination plots
MCMC-recover

Compare MCMC estimates to "true" parameter values
MCMC-parcoord

Parallel coordinates plot of MCMC draws
MCMC-diagnostics

General MCMC diagnostics
MCMC-scatterplots

Scatterplots of MCMC draws
MCMC-traces

Trace plots of MCMC draws
PPC-test-statistics

PPC test statistics
PPC-errors

PPC errors
PPC-distributions

PPC distributions
PPC-intervals

PPC intervals
PPC-loo

LOO predictive checks
PPC-scatterplots

PPC scatterplots
PPC-overview

Graphical posterior predictive checking
available_ppc

Get or view the names of available plotting functions
theme_default

Default bayesplot plotting theme
reexports

Objects exported from other packages
bayesplot-colors

Set, get, or view bayesplot color schemes
tidy-params

Tidy parameter selection
bayesplot-extractors

Extract quantities needed for plotting from model objects
PPC-censoring

PPC censoring
bayesplot-helpers

Convenience functions for adding or changing plot details
bayesplot-package

bayesplot: Plotting for Bayesian Models
PPC-discrete

PPCs for discrete outcomes
bayesplot_theme_get

Get, set, and modify the active bayesplot theme
bayesplot_grid

Arrange plots in a grid
example-data

Example draws to use in demonstrations and tests
pp_check

Posterior (or prior) predictive checks (S3 generic and default method)