Learn R Programming

⚠️There's a newer version (0.19-4.1) of this package.Take me there.

coda (version 0.19-1)

Output Analysis and Diagnostics for MCMC

Description

Provides functions for summarizing and plotting the output from Markov Chain Monte Carlo (MCMC) simulations, as well as diagnostic tests of convergence to the equilibrium distribution of the Markov chain.

Copy Link

Version

Install

install.packages('coda')

Monthly Downloads

147,224

Version

0.19-1

License

GPL (>= 2)

Maintainer

Last Published

December 8th, 2016

Functions in coda (0.19-1)

Autocorrelation function for Markov chains

Convert WinBUGS data file to JAGS data file

Coerce mcmc object to time series

Batch Standard Error

Cross correlations for MCMC output

The Cramer-von Mises Distribution

Main menu driver for the coda package

Options settings for the codamenu driver

Gelman-Rubin-Brooks plot

Gelman and Rubin's convergence diagnostic

Geweke's convergence diagnostic

Geweke-Brooks plot

Probability density function estimate from MCMC output

Effective sample size for estimating the mean

Heidelberger and Welch's convergence diagnostic

Highest Posterior Density intervals

Summary plots of mcmc objects

Dimensions of MCMC objects

Replicated Markov Chain Monte Carlo Objects

Markov Chain Monte Carlo Objects

Simple linear regression example

Estimate spectral density at zero

Conversions of MCMC objects

Estimate spectral density at zero

Read CODA output files produced by OpenBUGS

Trace plot of MCMC output

Time attributes for mcmc objects

Rejection Rate for Metropolis--Hastings chains

Named dimensions of MCMC objects

Trellis plots for mcmc objects

Mcpar attribute of MCMC objects

Choose multiple options from a menu

read.coda.interactive

Read CODA output files interactively

Thinning interval

Summary statistics for Markov Chain Monte Carlo chains

Read output files in CODA format

Plot image of correlation matrix

Cumulative quantile plot

Extract or replace parts of MCMC objects

Upgrade mcmc objects in obsolete format

Raftery and Lewis's diagnostic

Read data interactively and check that it satisfies conditions

Time windows for mcmc objects

Autocorrelation function for Markov chains

Plot autocorrelations for Markov Chains