# Functions to graphically assess the convergence of the MCMC-simulation in a MCmcmc object

### Description

These functions display traces, posterior densities and autocorrelation functions for the relevant subset of the parameters in a MCmcmc object.

### Usage

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ```
## S3 method for class 'MCmcmc'
trace( obj, what = "sd",
scales = c("same", "free"),
layout = "col",
aspect = "fill", ...)
## S3 method for class 'MCmcmc'
post( obj, what ="sd",
check = TRUE,
scales = "same",
layout = "row",
lwd = 2,
col,
plot.points = FALSE,
aspect = "fill", ... )
## S3 method for class 'MCmcmc'
pairs( x, what = "sd",
subset,
col = NULL,
pch = 16,
cex = 0.2,
scales = "free", ... )
``` |

### Arguments

`obj` |
A |

`x` |
A |

`what` |
Character indicating what parameters to plot.
Possible values are |

`scales` |
Character vector of length two, with possible values "same" or
"free", indicating whether x- and y-axes of the plots should be
constrained to be the same across panels. For |

`layout` |
Character. If |

`aspect` |
How should the panels be scaled. Default ( |

`check` |
Logical. Should the density plots be separate for each chain (in order to check convergence) or should the chains be merged. |

`lwd` |
Width of the lines used for plotting of the posterior densities. |

`col` |
Color of the lines points used for plotting of the posterior densities. |

`plot.points` |
Logical. Should a rug with actual data points be plotted beneath the density. |

`pch` |
Plot symbol for the points. |

`subset` |
Character or numerical indicating the columns of the posterior
that should be plotted by |

`cex` |
Plot character size for points in |

`...` |
Further aruments passed on to the |

### Details

A `Lattice`

plot is returned, which means that it must
`print`

ed when these functions are called in a batch program or
inside another function or for-loop.

`trace`

plots traces of the sampled chains,
`post`

plots posterior densities of the parameters and
`pairs`

plots a scatter-plot matrix of bivariate marginal
posterior distributions.

### Value

A `Lattice`

plot.

### Author(s)

Bendix Carstensen, Steno Diabetes Center, bxc@steno.dk, http://BendixCarstensen.com.

### See Also

`MCmcmc`

,
`plot.MCmcmc`

,
`ox.MC`

,
`sbp.MC`

### Examples

1 2 3 4 | ```
# Load a provided MCmcmc object
data( ox.MC )
trace.MCmcmc( ox.MC, what="beta" )
pairs.MCmcmc( ox.MC, what="sd" )
``` |