Orthogonalizepls

Purpose

Condenses y-variance into first component of a PLS model.

Synopsis

omodel = orthogonalizepls(model,x,y) %orthogonalize model

omodel = orthogonalizepls(omodel,x) %calculate scores for applying omodel to x

(This feature is also available from the Analysis window Tools menu)

Description

Produces an orthogonal PLS model which contains all the y-variance capturing direction in the first weight and loading. The predictions of the model are identical to the non-orthogonalized model but the loadings and weights have been rotated.

If no y-block information is passed, it is assumed that the model has already been orthogonalized and is being applied to the passed x-block data. In this case, only the new scores are calculated.

Inputs

• model = Standard PLS model to orthogonalize OR orthogonalized model (if no y passed)
• x = Preprocessed x-block data. Preprocessed in the same way as is indicated in the model.

Optional Inputs

• y = Preprocessed y-block data. If omitted, x is assumed to be NEW data to which the model is being applied. Otherwise, x and y are assumed to be the calibration data from which the model was created and model will be orthogonalized.

Outputs

• omodel = Model with orthogonalized loadings and scores.

See Also

cov_cv, glsw, pcr, pls