qb.BayesFactor {qtlbim} | R Documentation

## Bayesian model selection via Bayes factors.

### Description

Model-averaged posteriors and Bayes factors computed for number and pattern of QTL, chromosomes and pairs of chromosomes showing epistasis.

### Usage

    qb.BayesFactor(qbObject, items = c("nqtl","pattern","chrom","pairs"),
      cutoff.pattern = 0.2, cutoff.pairs = 1, nmax = 15)
    ## S3 method for class 'qb.BayesFactor':
    plot(x, ...)
    ## S3 method for class 'qb.BayesFactor':
    summary(object, sort = TRUE, digits = 3, ...)
    ## S3 method for class 'qb.BayesFactor':
    print(x, ...)

### Arguments

`qbObject` | An object of class `qb`.
`object` | Object of class `qb.BayesFactor`.
`x` | Object of class `qb.BayesFactor`.
`items` | Items to include in model selection assessment.
`cutoff.pattern` | Percent cutoff for pattern inclusion in model selection.
`cutoff.pairs` | Percent cutoff for epistatic pair inclusion in model selection.
`nmax` | Maximum number of model terms included per item (for `items` "pattern" and "pairs" only).
`sort` | Sort by Bayes factor if `TRUE`.
`digits` | Number of significant digits for summary.
`...` | Additional arguments passed to generic plot, summary or print.

### Details

`qb.BayesFactor` creates model selection results for selected items. These are based on marginal posteriors and priors, averaged over all other model parameters. The posterior may be influenced by prior, while Bayes factors are empirically less sensitive for QTL model selection. The Bayes factors are computed relative to the smallest term for each item, using the ratios of `posterior/prior`. Any pair of model terms can be compared as the ratio of their Bayes factors. The `items` evaluated are:

nqtl
  Number of QTLs.
pattern
  Pattern of QTL across chromosomes. Identifiers are comma-separated chromosome numbers, with asterisk `n*` for multiple QTL per chromosome.
chrom
  Chromosome.
pairs
  Epistatic pairs of chromosomes.

### Value

List with `items`, each containing:

`posterior` | Posterior frequency of MCMC samples.
`prior` | Prior frequency.
`bf` | Rank-ordered Bayes factors relative to smallest value.
`bfse` | Approximate standard error for bf computed using binomial variance of MCMC samples.

### Author(s)

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

### References

http://www.qtlbim.org

### See Also

`plot.qb`, `qb.mcmc`

### Examples

    temp <- qb.BayesFactor(qbExample)
    summary(temp)
    plot(temp)

[Package qtlbim version 1.6.5 Index]