From Eigenvector Research Documentation Wiki
Revision as of 09:21, 2 September 2008 by imported>Jeremy (Importing text file)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigation Jump to search


Generates a matrix used to calculate residuals from a single data block using partial least squares regression models with cross vaildation.


coeff = plsrsgcv(data,lv,cvit,cvnum,out)


coeff = plsrsgncv(data,lv,cvit,cvnum) calculates a matrix coeff from a single data block data. plsrsgncv calculates partial least squares regression models of each variable in the matrix data using the remaining variables and cross-validation with random test data blocks. The maximum number of latent variables to consider is lv, the number of test sets is cvit, and the number of samples in each test set is cvnum. Multiplying a new data matrix by the matrix coeff yields a matrix whose values are the difference between the new data and it's prediction based on the PLS regressions created by plsrsgncv.

See Also

plsrsgn, replace