Maximum likelihood discriminant analysis using the multivariate Cauchy distribution {mvcauchy}

Maximum likelihood discriminant analysis using the multivariate Cauchy distribution

Description

Maximum likelihood discriminant analysis using the multivariate Cauchy distribution.

Usage

mvcauchy.da(xnew, x, ina, mod = NULL)

Arguments

xnew

A numerical matrix with the new data whose class is to predicted. The rows correspond to observations and the columns to variables.

x

A numerical matrix with the data. The rows correspond to observations and the columns to variables.

ina

Should the logarithm of the density be returned (TRUE) or not (FALSE)?

mod

This is a list with the estimated parameters of each class obtained from the function mvcauchy.mle. If this is not available, then the function will compute the location and scatter from the available data.

Details

Maximum likelihood discriminant analysis using the multivariate Cauchy distribution is performed.

Value

A list including:

mod

A list with the output produced by mvcauchy.mle, for each class.

prob

The estimated probabilities of the new data of belonging to each group.

est

he estimated group membership of the new data.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

References

Kanti V. Mardia, John T. Kent and John M. Bibby (1979). Multivariate analysis. Academic Press, London.

See Also

rmvcauchy, mvcauchy.mle

Examples

x <- as.matrix(iris[, 1:4])
ina <- iris[, 5]
a <- mvcauchy.da(x, x, ina)