Partial Least Squares Discriminant Analysis

plsda {stats}

R Documentation

Partial Least Squares Discriminant Analysis

Description

plsda is used to calibrate, validate and use of partial least squares discrimination analysis (PLS-DA) model.

Usage

plsda(x, y,
    ncomp = NULL,
    center = TRUE,
    scale = FALSE,
    list = TRUE);

Arguments

matrix with predictors. [as dataframe]

vector with class membership (should be either a factor with class names/numbers in case of multiple classes Or a vector with logical values in case of one class model).

ncomp

maximum number Of components To calculate. [as integer]

center

logical, center or not predictors and response values. [as boolean]

scale

logical, scale (standardize) or not predictors and response values. [as boolean]

list

this function will returns a R# list that contains result data of the PLS-DA analysis by default, or the raw .NET clr object of the PLS result if this parameter value set to FALSE. [as boolean]

env

[as Environment]

Authors

sciBASIC.NET

Value

this function returns data object of type list. the list data also has some specificied data fields: list(component, scoreMN, loadingMN).

clr value class

list

[Package stats version 5.0.1.2389 Index]