dtrids: Jacobian Matrix of the Tri-PLS regression coefficients

In SvenSerneels/tripls_r: Trilinear partial least squares regression

Description

This function computes the Jacobian matrix of the Tri-PLS vector of regression coefficients with respect to the vector of cross products.

Usage

dtrids(X, y, p, q, h)

Arguments

X	The unfolded X data as a matrix (n x pq).
y	The corresponding y data as an n x 1 vector or a length n numeric
p	The number of variables in the p mode (integer)
q	The number of variables in the q mode (integer)
h	The number of latent variables to compute (integer)

Value

The Jacobian matrix db/ds (pq x pq)

Author(s)

Sven Serneels, BASF Corp.

References

S. Serneels, K. Faber, T. Verdonck, P.J. Van Espen, Case specific prediction intervals for tri-PLS1: The full local linearization. Chemometrics and Intelligent Laboratory Systems, 108 (2011), 93-99.

Examples

data(data_3)
J <- dtrids(array(data_3$X3,dim=c(17,33)),data_3$y3,11,3,2)

SvenSerneels/tripls_r documentation built on May 4, 2019, 6:30 a.m.