mvdalab (version 1.7)

mvdaloo: Leave-one-out routine for mvdareg objects

Description

When validation = 'loo' this routine effects the leave-one-out cross-validation procedure for mvdareg objects.

Usage

mvdaloo(X, Y, ncomp, weights = NULL, method = "bidiagpls", 
        scale = FALSE, boots = NULL, ...)

Value

Provides the following bootstrapped results as a list for mvdareg objects:

cvR2

leave-one-out estimate of cvR2.

PRESS

leave-one-out estimate of prediction error sums of squares.

MSPRESS

leave-one-out estimate of mean squared error prediction sums of squares.

RMSPRESS

leave-one-out estimate of mean squared error prediction sums of squares.

in.bag

leave-one-out samples used for model building.

Arguments

X

a matrix of observations. NAs and Infs are not allowed.

Y

a vector. NAs and Infs are not allowed.

ncomp

the number of components to include in the model (see below).

weights

currently not in use

method

PLS algorithm used

scale

scaling used

boots

not applicable for validation = 'loo'

...

additional arguments. Currently ignored.

Author

Nelson Lee Afanador (), Thanh Tran ()

Details

This function should not be called directly, but through the generic function plsFit with the argument validation = 'loo'.

References

NOTE: This function is adapted from mvr in package pls with extensive modifications by Nelson Lee Afanador and Thanh Tran.

See Also

plsFit, mvdaboot

Examples

data(Penta)
mod1 <- plsFit(log.RAI ~., scale = TRUE, data = Penta[, -1], 
        ncomp = 2, method = "bidiagpls", validation = "loo")

mod1$validation$cvR2
mod1$validation$PRESS
mod1$validation$MSPRESS
mod1$validation$RMSPRESS
mod1$validation$in.bag