# Summarise and plot tabular MCMC output

### Description

This function summarises and plots tabular MCMC output such as that generated by the function normgibbs

### Usage

1 2 | ```
mcmcAnalysis(mat, rows = 4, lag.max = 100, bins = 30,
show = TRUE, plot = TRUE)
``` |

### Arguments

`mat` |
Matrix of MCMC output, where the columns represent variables and the rows represent iterations |

`rows` |
Number of variables to plot per page on the graphics device |

`lag.max` |
Maximum lag for the ACF plots |

`bins` |
Approximate number of bins to use for the histograms |

`show` |
If TRUE, will display numerical summaries on the R console |

`plot` |
If TRUE, will plot graphical summaries on the default graphics device |

### Author(s)

A version of mcmcSummary in Darren Wilkinson's package smfsb

### Examples

1 2 | ```
posterior=gibbsNormal(N=1000,initial=c(10,0.25),priorparam=c(10,1/100,3,12),n=100,xbar=15,s=4.5)
mcmcAnalysis(posterior,rows=2,bins=10)
``` |

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker. Vote for new features on Trello.