qb.BayesFactor {qtlbim} | R Documentation |
Model-averaged posteriors and Bayes factors computed for number and pattern of QTL, chromosomes and pairs of chromosomes showing epistasis.
qb.BayesFactor(qbObject, items = c("nqtl","pattern","chrom","pairs"), cutoff.pattern = 0.2, cutoff.pairs = 1, nmax = 15) ## S3 methods. plot.qb.BayesFactor(x, ...) summary.qb.BayesFactor(object, sort = TRUE, digits = 3, ...) print.qb.BayesFactor(x, ...)
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. |
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:
n*
for
multiple QTL per chromosome.
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. |
Brian S. Yandell, yandell@stat.wisc.edu
temp <- qb.BayesFactor(qbExample) summary(temp) plot(temp)