plot.bim.model {bim} | R Documentation |
Model-averaged posteriors and posterior/prior ratios for graphical Bayes factor assessment. First row concerns number of QTL, second row evaluates pattern of QTL across chromosomes.
plot.bim.model( x, cross, nqtl = 1, pattern=NULL, exact=FALSE, cutoff = 1, assess, ... )
x |
object of class bim or class bim.model |
cross |
corresponding object of class cross |
nqtl |
subset on number of QTL |
pattern |
subset on chromosome pattern of QTL |
exact |
subset on exact pattern or number of QTL if true |
cutoff |
percent cutoff for inclusion in model selection |
assess |
object of class bim.model from bim.model |
... |
graphical parameters can be given as arguments to
plot |
plot.bim.model
uses results (assess
) of bim.model
and arranges plots on a single page. If x
is of class
bim.model
, then assess
is set to its value and the other
arguments are ignored. Left plot is of posterior against model
identifier, while right plot assesses Bayes factors. Since Bayes
factors are ratios of posterior/prior
ratios, a semi-log plot
of posterior/prior
against model identifier (m = number
of QTL or M = model pattern) provides a graphical model
assessment tool with a BF threshold yardstick.
Brian S. Yandell, yandell@stat.wisc.edu
http://www.stat.wisc.edu/~yandell/qtl/software/bmqtl
data( vern ) data( verngeo.bim ) plot.bim.model( verngeo.bim, vern, 2 )