README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

nformat <- function(x)
  format(x, big.mark = ',')
```


# mcgibbsit

<!-- badges: start -->
[![CRAN status](https://www.r-pkg.org/badges/version/mcgibbsit)](https://CRAN.R-project.org/package=mcgibbsit)
[![Lifecycle: stable](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable)
<!-- badges: end -->

Implementation of Warnes & Raftery's `MCGibbsit` run-length diagnostic
for a set of (not-necessarily independent) Markov Chain Monte Carlo (MCMC) samplers.  

It combines the estimate error-bounding approach of the Raftery and Lewis MCMC
run length diagnostic (`gibbsit`) with the between verses within chain approach of the Gelman and Rubin MCMC convergence diagnostic.

## Installation

Install the most recent release from `CRAN`:
``` r
install.packages("mcgibbsit")
```

Or the current development version from `github`:
```r
if(!require("remotes"))
  install.packages("remotes")
  
remotes::install_github('r-gregmisc/mcgibbsit')
```

```{r, child='vignettes/mcgibbsit_example.Rmd'}
```