plot.bim.diag {bim} | R Documentation |

## Marginal and model-conditional summaries of Bayesian interval
mapping diagnostics

### Description

A density histogram is drawn for model-averaged summary diagnostics such
as LOD, variance, or heritability.

### Usage

plot.bim.diag(x, nqtl=1, pattern=NULL, exact=FALSE,
items=<<see below>>, mains=items,
mfrow=<<see below>>, ... )

### Arguments

`x` |
object of class `bim` |

`nqtl` |
subset on number of QTL |

`pattern` |
subset on chromosome pattern of QTL |

`exact` |
subset on exact pattern or number of QTL if true |

`items` |
diagnostics to be summarized; must be column of data |

`mains` |
titles for items |

`mfrow` |
plot arrangement parameter for `par()` (default is
rows = number of items by cols = 2) |

`...` |
graphical parameters can be given as arguments to `plot` |

### Details

Model-averaged density is smooth kernel estimate similar to ordinary
histogram. A `boxplot`

(without outliers) is
overlaid for comparison with conditional boxplots. Conditional
boxplots by number of QTL may show indication of model bias for
small number of QTL. This and `bim.nqtl`

can help
suggest the minimal model. Diagnostic items that make sense to plot
are `"LOD"`

, `"envvar"`

(environmental variance),
`"herit"`

(heritability), `"mean"`

(grand mean),
`"addvar"`

(variance of `add`

), `"domvar"`

(variance of
`add`

). Marginal and conditional medians are printed.

### Author(s)

Brian S. Yandell, yandell@stat.wisc.edu

### References

http://www.stat.wisc.edu/~yandell/qtl/software/Bmapqtl

### See Also

`plot.bim`

, `density`

, `boxplot`

### Examples

data( verngeo.bim )
plot.bim.diag( verngeo.bim, 2, items = c("LOD","herit") )

[Package

*bim* version 1.01-1

Index]