plsRglm (version 0.7.4)

infcrit.dof: Information criteria

Description

This function computes information criteria for existing plsR model using Degrees of Freedom estimation.

Usage

infcrit.dof(modplsR, naive = FALSE)

Arguments

modplsR

A plsR model i.e. an object returned by one of the functions plsR, plsRmodel.default, plsRmodel.formula, PLS_lm or PLS_lm_formula.

naive

A boolean.

Value

• matrix
  AIC, BIC and gmdl values or NULL.

Details

If naive=FALSE returns AIC, BIC and gmdl values for estimated and naive degrees of freedom. If naive=TRUE returns NULL.

References

M. Hansen, B. Yu, Model Selection and Minimum Descripion Length Principle, Journal of the American Statistical Association, 96 (2001) 746-774. N. Kraemer, M. Sugiyama, The Degrees of Freedom of Partial Least Squares Regression. Preprint (2010). http://arxiv.org/abs/1002.4112. N. Kraemer, M.L. Braun, Kernelizing PLS, Degrees of Freedom, and Efficient Model Selection, Proceedings of the 24th International Conference on Machine Learning, Omni Press, (2007) 441-448.

See Also

plsR.dof for degrees of freedom computation and infcrit.dof for computing information criteria directly from a previously fitted plsR model.

Examples

data(Cornell)
XCornell<-Cornell[,1:7]
yCornell<-Cornell[,8]
modpls <- plsR(yCornell,XCornell,4)
infcrit.dof(modpls)