dda: Dirichlet discriminant analysis

In Compositional: Compositional Data Analysis

Dirichlet discriminant analysis

Description

Dirichlet discriminant analysis.

Usage

dda(xnew, x, ina)

Arguments

xnew	A matrix with the new compositional predictor data whose class you want to predict. Zeros are allowed.
x	A matrix with the available compositional predictor data. Zeros are allowed.
ina	A vector of data. The response variable, which is categorical (factor is acceptable).

Details

The funcitons performs maximum likelihood discriminant analysis using the Dirichlet distribution.

Value

A vector with the estimated group.

Author(s)

Michail Tsagris.

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

References

Friedman J., Hastie T. and Tibshirani R. (2017). The elements of statistical learning. New York: Springer.

Thomas P. Minka (2003). Estimating a Dirichlet distribution. http://research.microsoft.com/en-us/um/people/minka/papers/dirichlet/minka-dirichlet.pdf

Ng Kai Wang, Guo-Liang Tian and Man-Lai Tang (2011). Dirichlet and related distributions: Theory, methods and applications. John Wiley & Sons.

Aitchison J. (1986). The statistical analysis of compositional data. Chapman & Hall.

See Also

cv.dda, comp.nb, alfa.rda, alfa.knn, comp.knn, mix.compnorm, diri.reg, zadr

Examples

x <- Compositional::rdiri(100, runif(5) )
ina <- rbinom(100, 1, 0.5) + 1
mod <- dda(x, x, ina )

Compositional documentation built on Oct. 23, 2023, 5:09 p.m.