POCRE (version 0.6.0)

selectmodel: Select the Optimal Model

Description

Select the optimal model from those fitted by POCRE, on the basis of prespecified criterion, such as EBIC, BIC, AIC, and AICc.

Usage

selectmodel(ppobj, msc=NULL)

Arguments

ppobj

output from pocrepath.

msc

a value indicating the information criterion: 0 for BIC, (0,1] for EBIC (by default), 2 for AIC, 3 for AICc.

Value

output of pocre for the optimal model.

References

Chen J and Chen Z (2008) Extended Bayesian information criteria for model selection with large model spaces. Biometrika, 95: 759-771.

Zhang D, Lin Y, and Zhang M (2009). Penalized orthogonal-components regression for large p small n data. Electronic Journal of Statistics, 3: 781-796.

See Also

pocrepath, plot.pocrepath.

Examples

# NOT RUN {
data(simdata)
xx <- scale(as.matrix(simdata[,-1]))
yy <- scale(as.matrix(simdata[,1]))

# ppres <- pocrepath(yy,xx,delta=0.01)
ppres <- pocrepath(yy,xx)
fres <- selectmodel(ppres)
# }