get_weights: Computes the weights for pls regressions

In resemble: Memory-Based Learning in Spectral Chemometrics

Computes the weights for pls regressions

Description

This is an internal function that computes the wights required for obtaining each vector of pls scores. Implementation is done in C++ for improved performance.

Usage

get_weights(X, Y, algorithm = "pls", xls_min_w = 3L, xls_max_w = 15L)

Arguments

X	a numeric matrix of spectral data.
Y	a matrix of one column with the response variable.
algorithm	a character string indicating what method to use. Options are: 'pls' for pls (using covariance between X and Y), 'mpls' for modified pls (using correlation between X and Y as in Shenk and Westerhaus, 1991; Westerhaus 2014) or 'xls' for extended pls (as implemented in BUCHI NIRWise PLUS software).
xls_min_w	an integer indicating the minimum window size for the "xls" method. Only used if algorithm = 'xls'. Default is 3 (as in BUCHI NIRWise PLUS software).
xls_max_w	an integer indicating the maximum window size for the "xls" method. Only used if algorithm = 'xls'. Default is 15 (as in BUCHI NIRWise PLUS software).

Value

a matrix of one column containing the weights.

Author(s)

Leonardo Ramirez-Lopez and Claudio Orellano

References

Shenk, J. S., & Westerhaus, M. O. (1991). Populations structuring of near infrared spectra and modified partial least squares regression. Crop Science, 31(6), 1548-1555.

Westerhaus, M. (2014). Eastern Analytical Symposium Award for outstanding Wachievements in near infrared spectroscopy: my contributions to Wnear infrared spectroscopy. NIR news, 25(8), 16-20.

resemble documentation built on May 29, 2024, 8:49 a.m.