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mcmcse (version 1.3-2)

Monte Carlo Standard Errors for MCMC

Description

Provides tools for computing Monte Carlo standard errors (MCSE) in Markov chain Monte Carlo (MCMC) settings. MCSE computation for expectation and quantile estimators is supported as well as multivariate estimations. The package also provides functions for computing effective sample size and for plotting Monte Carlo estimates versus sample size.

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Version

Install

install.packages('mcmcse')

Monthly Downloads

1,537

Version

1.3-2

License

GPL (>= 2)

Homepage

http://faculty.ucr.edu/~jflegal

Maintainer

Dootika Vats

Last Published

July 4th, 2017

Functions in mcmcse (1.3-2)

Apply mcse to each column of a matrix or data frame of MCMC samples.

Multivariate Monte Carlo standard errors for expectations.

Confidence regions (ellipses) for Monte Carlo estimates

Estimate effective sample size (ESS) as described in Gong and Felgal (2015).

Compute Monte Carlo standard errors for quantiles.

Apply mcse.q to each column of a matrix or data frame of MCMC samples.

Create a plot that shows how Monte Carlo estimates change with increasing sample size.

Monte Carlo Standard Errors for MCMC

Compute Monte Carlo standard errors for expectations.

Multivariate Monte Carlo standard errors for expectations with the initial sequence method of Dai and Jones (2017).

Minimum effective sample size required for stable estimation as described in Vats et al. (2015).

Effective Sample Size of a multivariate Markov chain as described in Vats et al. (2015).

QQplot for Markov chains