anal.leaps | R Documentation |
Analyze a backcross using forward or backward selection or either of these followed by branch-and-bound.
anal.leaps(dat, method=c("forward","backward","forwback",
"forwardleap","backwardleap"),
bic.mult=2.5, max.steps=30)
dat |
The data: a list with components |
method |
Model search approach to use: forward selection, backward elimination, forward selection followed by backward elimination, or forward or backward selection followed by branch-and-bound. |
bic.mult |
Multiplier for BIC, for choosing the size of the model. |
max.steps |
Maximum number of steps in forward selection. |
A list whose first component is a vector indicating the marker columns selected and second component is the corresponding BIC-delta value.
Karl W Broman, broman@wisc.edu
Broman, K. W. (1997) Identifying quantitative trait loci in experimental crosses. PhD dissertation, Department of Statistics, University of California, Berkeley.
simbc
, anal.all
,
anal.mcmc
, perm
dat <- simbc(n.ind=100,qtl.eff=c(1,1,1,-1,1,1,1)*0.75)
results <- anal.leaps(dat,method="forwback",bic.mult=2.56)
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