plotModelsize {BMS} | R Documentation |

## Plot Model Size Distribution

### Description

Plots posterior and prior model size distribution

### Usage

```
plotModelsize(
bmao,
exact = FALSE,
ksubset = NULL,
include.legend = TRUE,
do.grid = TRUE,
...
)
```

### Arguments

`bmao` |
a 'bma' object (cf. |

`exact` |
if |

`ksubset` |
integer vector detailing for which model sizes the plot should be done |

`include.legend` |
if |

`do.grid` |
if |

`...` |
parameters passed on to |

### Value

As a default, `plotModelsize`

plots the posterior model size
distribution as a blue line, and the prior model distribution as a dashed
red line.

In addition, it returns a list with the following elements:

`mean` |
The posterior expected value of model size |

`var` |
The variance of the posterior model size distribution |

`dens` |
A vector
detailing the posterior model size distribution from model size |

### See Also

See also `bms`

, `image.bma`

,
`density.bma`

, `plotConv`

Check http://bms.zeugner.eu for additional help.

### Examples

```
data(datafls)
mm=bms(datafls,burn=1500, iter=5000, nmodel=200,mprior="fixed",mprior.size=6)
#plot Nb.1 based on aggregate results
postdist= plotModelsize(mm)
#plot based only on 30 best models
plotModelsize(mm[1:30],exact=TRUE,include.legend=FALSE)
#plot based on all best models, but showing distribution only for model sizes 1 to 20
plotModelsize(mm,exact=TRUE,ksubset=1:20)
# create a plot similar to plot Nb. 1
plot(postdist$dens,type="l")
lines(mm$mprior.info$mp.Kdist)
```

*BMS*version 0.3.5 Index]