Cross-validation for the Dirichlet discriminant analysis {Compositional} R Documentation

## Cross-validation for the Dirichlet discriminant analysis

### Description

Cross-validation for the Dirichlet discriminant analysis.

### Usage

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

### Arguments

 `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.

### Details

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

### Value

A list including:

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

### Author(s)

Michail Tsagris

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

### 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

### See Also

``` dda, alfanb.tune, alfarda.tune, compknn.tune, cv.compnb ```

### Examples

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

[Package Compositional version 5.2 Index]