reg.mle.lda: Regularised maximum likelihood linear discriminant analysis

In Rfast2: A Collection of Efficient and Extremely Fast R Functions II

Regularised maximum likelihood linear discriminant analysis

Description

Regularised maximum likelihood linear discriminant analysis.

Usage

reg.mle.lda(xnew, x, ina, lambda)

Arguments

xnew	A numerical vector or a matrix with the new observations, continuous data.
x	A matrix with numerical data.
ina	A numerical vector or factor with consecutive numbers indicating the group to which each observation belongs to.
lambda	A vector of regularization values \lambda such as (0, 0.1, 0.2,...).

Details

Regularised maximum likelihood linear discriminant analysis is performed. The function is not extremely fast, yet is pretty fast.

Value

A matrix with the predicted group of each observation in "xnew". Every column corresponds to a \lambda value. If you have just on value of \lambda, then you will have one column only.

Author(s)

Michail Tsagris.

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

See Also

regmlelda.cv mle.lda, fisher.da, big.knn, weibull.nb

Examples

x <- as.matrix(iris[, 1:4])
ina <- iris[, 5]
a <- reg.mle.lda(x, x, ina, lambda = seq(0, 1, by = 0.1) )

Rfast2 documentation built on Aug. 8, 2023, 1:11 a.m.