ctmva (version 1.6.0)

lda.ct: Continuous-time Fisher's linear discriminant analysis

Description

A continuous-time version of Fisher's LDA, in which segments of the time interval take the place of groups of observations.

Usage

lda.ct(fdobj, partition, part.names = NULL)

Value

Object of class "lda.ct", a list consisting of

means

means of the variables within each segment

scaling

matrix of coefficients defining the discriminants (as in lda)

values

eigenvalues giving the ratios of between to within sums of squares

partition

the supplied partition

fdobj

linear discriminants represented as an "fd" object

nld

number of linear discriminants

Arguments

fdobj

continuous-time multivariate data set of class "fd"

partition

a priori break points dividing the time interval into segments

part.names

optional character vector of names for the segments

Author

Biplab Paul <[e-mail]> and Philip Tzvi Reiss <[e-mail]>

Details

The means and scaling components of the output are similar to lda, but unlike that function, lda.ct performs only Fisher's LDA and cannot incorporate priors or perform classification.

See Also

plot.lda.ct; lda, for the classical version

Examples

## see end of example in ?pca.ct