selectmodel: Select the Optimal Model

In POCRE: Penalized Orthogonal-Components Regression

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.

Author(s)

Dabao Zhang, Zhongli Jiang, Zeyu Zhang, Department of Statistics, Purdue University

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

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)

POCRE documentation built on March 18, 2022, 6:43 p.m.