optim.GSCA(matrixpls.res)matrixpls from which the
criterion function is calculatedThe matrixpls implementation of the GSCA criterion extends the criterion
presented by Huang and Takane by including also the minimization of the
residual variances of the formative part of the model. The formative
regressions in a model are typically specified to be identical to the
weight pattern W.mod resulting zero residual variances by definition.
However, it is possible to specify a formative model that does not completely
overlap with the weight pattern leading to non-zero residuals that can be
optimizes.
inner.GSCA;
outer.GSCAOther Weight optimization criteria: optim.GCCA;
optim.maximizeInnerR2;
optim.maximizePrediction