cols (version 1.5)

Positively constrained least squares with a multivariate response: Positively constrained least squares with a multivariate response

Description

Positively constrained least squares with a multivariate response.

Usage

mvpls(y, x)

Value

A list including:

be

The positively constrained beta coefficients.

mse

The mean squared error.

Arguments

y

The response variables, a numerical matrix with observations.

x

A matrix with independent variables, the design matrix.

Author

Michail Tsagris.

R implementation and documentation: Michail Tsagris .

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 \(\beta_{jk}\geq 0\).

See Also

cls

Examples

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