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crcvrnd
Purpose
Cross-validation for continuum regression models using SDEP.
Synopsis
[press,fiterr,mlvp,b] = crcvrnd(x,y,splt,itr,lv,pwrs,ss,mc)
Description
crcvrnd is used to cross-validate continuum regression models given a matrix of predictor
variables (x-block) x, matrix or vector of predicted variables (y-block) y, the number of
divisions into which to split the data splt, the number of iterations of the cross-validation
procedure using different re-orderings of the data set itr, maximum number of latent
variables lv and the row vector of continuum regression parameters to consider powers.
The outputs are the predictive residual error sum of squares (PRESS) matrix press where
each element of the matrix represents the PRESS for a given combination of LVs and
continuum parameter, the corresponding fit error fiterr, the number of LVs and power at
minimum PRESS mlvp and the final regression vector or matrix b.
The optional input ss causes the routine to choose contiguous blocks of data during crossvalidation when set to 1. If the optional input mc is set to 0 the subsets are not mean-centered
during cross-validation.
A good smooth PRESS surface can usuall be obtained by calculating about 20 models spaced
logarithmically between 4 and 1/4 and using 10 to 30 iterations of the cross-validation. A
good rule of thumb for dividing the data is to use either the square root of the number of
samples or 10, which ever is smaller.
See Also
cr, pcr, pls
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