ldaHmat {subselect}R Documentation

Total and Between-Group Deviation Matrices in Linear Discriminant Analysis

Description

Computes total and between-group matrices of Sums of Squares and Cross-Product (SSCP) deviations in linear discriminant analysis. These matrices may be used as input to the variable selection search routines anneal, genetic improve or leaps.

Usage


## Default S3 method:
ldaHmat(x,grouping,...)

## S3 method for class 'data.frame':
ldaHmat(x,grouping,...)

## S3 method for class 'formula':
ldaHmat(formula,data=NULL,...)

Arguments

x A matrix or data frame containing the discriminators for which the SSCP matrix is to be computed.
grouping A factor specifying the class for each observation.
formula A formula of the form 'groups ~ x1 + x2 + ...' That is, the response is the grouping factor and the right hand side specifies the (non-factor) discriminators.
data Data frame from which variables specified in 'formula' are preferentially to be taken.
... further arguments for the method.

Value

A list with four items:

mat The total SSCP matrix
H The between-groups SSCP matrix
r The expected rank of the H matrix which equals the minimum between the number of discriminators and the number of groups minus one. The true rank of H can be different from r if the discriminators are linearly dependent.
call The function call which generated the output.

See Also

anneal, genetic, improve, leaps, lda.

Examples

##--------------------------------------------------------------------

## An example with a very small data set. We consider the Iris data
## and three groups, defined by species (setosa, versicolor and
## virginica). 

data(iris)
ldaHmat(iris[1:4],iris$Species)


[Package subselect version 0.9-99 Index]