LdaClassic: Linear Discriminant Analysis

In rrcov: Scalable Robust Estimators with High Breakdown Point

Linear Discriminant Analysis

Description

Performs a linear discriminant analysis and returns the results as an object of class LdaClassic (aka constructor).

Usage

LdaClassic(x, ...)


## Default S3 method:
LdaClassic(x, grouping, prior = proportions, tol = 1.0e-4, ...)

Arguments

x	a matrix or data frame containing the explanatory variables (training set).
grouping	grouping variable: a factor specifying the class for each observation.
prior	prior probabilities, default to the class proportions for the training set.
tol	tolerance
...	arguments passed to or from other methods.

Value

Returns an S4 object of class LdaClassic

Author(s)

Valentin Todorov [e-mail]

References

Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32(3), 1–47. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v032.i03")}.

See Also

Lda-class, LdaClassic-class,

Examples

## Example anorexia
library(MASS)
data(anorexia)

## rrcov: LdaClassic()
lda <- LdaClassic(Treat~., data=anorexia)
predict(lda)@classification

## MASS: lda()
lda.MASS <- lda(Treat~., data=anorexia)
predict(lda.MASS)$class

## Compare the prediction results of MASS:::lda() and LdaClassic()
all.equal(predict(lda)@classification, predict(lda.MASS)$class)

rrcov documentation built on May 29, 2024, 1:13 a.m.