mvpls: Positively constrained least squares with a multivariate...

In cols: Constrained Ordinary Least Squares

Positively constrained least squares with a multivariate response

Description

Positively constrained least squares with a multivariate response.

Usage

mvpls(y, x)

Arguments

y	The response variables, a numerical matrix with observations.
x	A matrix with independent variables, the design matrix.

Details

The constraint is that all beta coefficients (including the constant) are positive, i.e. min \sum_{i=1}^n(\bm{y}_i-\bm{x}_i\bm{\beta})^\top(\bm{y}_i-\bm{x}_i\bm{\beta}) such that \beta_{jk}\geq 0.

Value

A list including:

be	The positively constrained beta coefficients.
mse	The mean squared error.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

See Also

cls

Examples

y <- as.matrix( iris[, 1:2] )
x <- as.matrix( iris[, 3:4] )
mvpls(y, x)

cols documentation built on April 3, 2025, 10:33 p.m.