subselect (version 0.15.5)

ldaHmat: 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 eleaps.

Usage

# S3 method for default
ldaHmat(x,grouping,...)
# S3 method for data.frame
ldaHmat(x,grouping,...)
# S3 method for formula
ldaHmat(formula,data=NULL,...)

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.

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.

See Also

anneal, genetic, improve, eleaps, 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)
irisHmat <- ldaHmat(iris[1:4],iris$Species)
irisHmat

##$mat
##             Sepal.Length Sepal.Width Petal.Length Petal.Width
##Sepal.Length   102.168333   -6.322667     189.8730    76.92433
##Sepal.Width     -6.322667   28.306933     -49.1188   -18.12427
##Petal.Length   189.873000  -49.118800     464.3254   193.04580
##Petal.Width     76.924333  -18.124267     193.0458    86.56993

##$H
##             Sepal.Length Sepal.Width Petal.Length Petal.Width
##Sepal.Length     63.21213   -19.95267     165.2484    71.27933
##Sepal.Width     -19.95267    11.34493     -57.2396   -22.93267
##Petal.Length    165.24840   -57.23960     437.1028   186.77400
##Petal.Width      71.27933   -22.93267     186.7740    80.41333

##$r
##[1] 2

##$call
##ldaHmat.data.frame(x = iris[1:4], grouping = iris$Species)