Polypls: Difference between revisions

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Revision as of 08:21, 2 September 2008

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. Inputs are a matrix of predictor variables (x-block) x, a matrix of predicted variables (y-block) y, the number of latent variables lv, and the order of the polynomial n. Outputs are p the x-block latent variable loadings, q the y-block variable loadings, w the x-block latent variable weights, t the x-block latent variable scores, u the y-block latent variable scores, b a matrix of polynomial coefficients for the inner relationship, and ssqdif a table of x- and y-block variance captured by the PLS model. Use POLYPRED to make predictions with new data.

See Also

lwrxy, pls, polypred