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

In ctmva: Continuous-Time Multivariate Analysis

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)

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

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.

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

Author(s)

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

See Also

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

Examples

## see end of example in ?pca.ct

ctmva documentation built on June 22, 2024, 12:27 p.m.