Compositional: cv.dda – R documentation

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cv.dda

Cross-validation for the Dirichlet discriminant analysis

Cross-validation for the Dirichlet discriminant analysis.

cv.dda(x, ina, nfolds = 10, folds = NULL, stratified = TRUE, seed = FALSE)

`x`	A matrix with the available data, the predictor variables.
`ina`	A vector of data. The response variable, which is categorical (factor is acceptable).
`folds`	A list with the indices of the folds.
`nfolds`	The number of folds to be used. This is taken into consideration only if "folds" is NULL.
`stratified`	Do you want the folds to be selected using stratified random sampling? This preserves the analogy of the samples of each group. Make this TRUE if you wish.
`seed`	If you set this to TRUE, the same folds will be created every time.

This function estimates the performance of the Dirichlet discriminant analysis via k-fold cross-validation.

A list including:

`percent`	The percentage of correct classification
`runtime`	The duration of the cross-validation proecdure.

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

x <- as.matrix(iris[, 1:4])
x <- x / rowSums(x)
mod <- cv.dda(x, ina = iris[, 5] )

Compositional Data Analysis

v4.6

GPL (>= 2)

Authors

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

Initial release

2021-04-27