pls.est: Partial least squares (PLS) algorithm

In tpepler/cpc: Common principal component (CPC) analysis and applications

Partial least squares (PLS) algorithm

Description

Implementation of the partial least squares (PLS) algorithm as described in Hastie et al. (2009).

Usage

pls.est(X, Y)

Arguments

X	Matrix containing the independent variables.
Y	Vector containing the dependent/response values.

Value

Returns a list with the following items:

pls.scores	The partial least squares scores.
pls.loadings	The partial least squares loadings.

Author(s)

Theo Pepler

References

Hastie, T., Tibshirani, R., and Friedman, J. (2009). The Elements of Statistical Learning. Springer.

Examples

# The Iris data
data(iris)
indep <- iris[, 1:3]
dep <- iris[, 4]
pls.est(X = indep, Y = dep)

tpepler/cpc documentation built on July 7, 2022, 2:13 a.m.