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bayesplot (version 1.2.0)

Plotting for Bayesian Models

Description

Plotting functions for posterior analysis, model checking, and MCMC diagnostics. 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

31,914

Version

1.2.0

License

GPL (>= 3)

Maintainer

Jonah Gabry

Last Published

April 12th, 2017

Functions in bayesplot (1.2.0)

MCMC-combos

Combination plots
MCMC-diagnostics

General MCMC diagnostics
MCMC-distributions

Histograms and kernel density plots of MCMC draws
MCMC-intervals

Plot interval estimates from MCMC draws
MCMC-nuts

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

Plots for Markov chain Monte Carlo simulations
MCMC-recover

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

Scatterplots of MCMC draws
MCMC-traces

Traceplot (time series plot) of MCMC draws
PPC-discrete

PPCs for discrete outcomes
PPC-test-statistics

PPC test statistics
available_ppc

Get or view the names of available plotting functions
bayesplot-colors

Set, get, or view color schemes
bayesplot-extractors

Extract quantities needed for plotting from model objects
PPC-overview

Graphical posterior predictive checking
PPC-scatterplots

PPC scatterplots
bayesplot_grid

Arrange plots in a grid
example-data

Example draws to use in demonstrations and tests
PPC-intervals

PPC intervals
PPC-loo

LOO predictive checks
bayesplot-helpers

Convenience functions for adding or changing plot details
PPC-distributions

PPC distributions
PPC-errors

PPC errors
pp_check

Posterior predictive checks (S3 generic and default method)
theme_default

Default plotting theme
bayesplot-package

Plots for Bayesian Models