structpls: Structural PLS

In mortenarendt/StructuralKnowledgeModl: Incorporation of Structural Knowledge in Multivariate Models

Description

Calculates a PLS model with a combined objective, maximising 1) covariance between X and Y, 2) description of feature to feature relationship, 3) Alternative kernel representation of sample-data and 4) with possible sparseness.

Usage

structpls(X, Y, lv, Q, H, aH, sumabsw, deflateX = FALSE)

Arguments

X	a (preprocessed) n by px dataset
Y	a (preprocessed) n by py dataset of responses
lv	number of components
Q	a py by py symmetric feature kernel representing similarities between features.
H	a px by px symmetric sample kernel representing similarities between samples.
sumabsw	a scalar contraint on the L1 norm of the weights.
deflateX	(=FALSE default) whether to deflate X in the iterative estimation of components. Y is always deflated.

mortenarendt/StructuralKnowledgeModl documentation built on May 21, 2019, 11:42 a.m.