Low-level function to perform the cross-validation in lsplsCv.
orthlsplsCv(Y, X, Z, ncomp, segments, trace = FALSE, …)matrix. Response matrix.
matrix. The first predictor matrix (typically a design matrix).
list. List of predictor matrices.
list. The number of components to fit from each matrix.
list. The segments to use.
logical; if TRUE, the segment number is printed
for each segment.
Further arguments. Currently not used.
An array of cross-validated predictions. The first dimension corresponds to the observations, the second to the responses, and the rest to the number of components of the PLS models.
This function is not meant to be called directly by the user. It performs cross-validation of ortogonalized LS-PLS-models without splitting of parallell matrices into common and unique components. See the references for details.
J<U+00F8>rgensen, K., Segtnan, V. H., Thyholt, K., N<U+00E6>s, T. (2004) A Comparison of Methods for Analysing Regression Models with Both Spectral and Designed Variables. Journal of Chemometrics, 18(10), 451--464.
J<U+00F8>rgensen, K., Mevik, B.-H., N<U+00E6>s, T. Combining Designed Experiments with Several Blocks of Spectroscopic Data. (Submitted)
Mevik, B.-H., J<U+00F8>rgensen, K., M<U+00E5>ge, I., N<U+00E6>s, T. LS-PLS: Combining Categorical Design Variables with Blocks of Spectroscopic Measurements. (Submitted)