Compositional: dda – R documentation

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dda

Dirichlet discriminant analysis

Dirichlet discriminant analysis.

dda(xnew, x, ina)

`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).

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

A vector with the estimated group.

Michail Tsagris.

R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.

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.

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

Compositional Data Analysis

v4.6

GPL (>= 2)

Authors

Michail Tsagris [aut, cre], Giorgos Athineou [aut], Abdulaziz Alenazi [ctb]

Initial release

2021-04-27