Polypls
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Purpose
Calculate partial least squares regression models with polynomial inner relations.
Synopsis
- [p,q,w,t,u,b,ssqdif] = polypls(x,y,lv,n)
Description
POLYPLS creates a partial least squares regression model with polynomial fit for the inner relation.
Use POLYPRED to make predictions with new data.
Inputs
- x = matrix of predictor variables (X-block),
- y = vector or matrix of the predicted variables (Y-block),
- lv = maximum number of latent variables to consider,
- n = order of polynomial to use for the inner-relation.
Outputs
- p = x-block loadings,
- q = y-block loadings,
- w = x-block weights,
- t = x-block scores,
- u = y-block scores,
- b = matrix of polynomial coefficients for the inner-relation,
- ssqdif = table of x- and y-block variance captured by the PLS model.
Options
options = a structure array with the following fields:
- plots: [ {'none'} | 'final' ] governs plotting of results, and
- order: positive integer for polynomial order {default = 1}.