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Directional (version 6.8)

BIC for the model based clustering using mixtures of von Mises-Fisher distributions: BIC to choose the number of components in a model based clustering using mixtures of von Mises-Fisher distributions

Description

BIC to choose the number of components in a model based clustering using mixtures of von Mises-Fisher distributions

Usage

bic.mixvmf(x, G = 5, n.start = 20)

Value

A plot of the BIC values and a list including:

BIC

The BIC values for all the models tested.

runtime

The run time of the algorithm. A numeric vector. The first element is the user time, the second element is the system time and the third element is the elapsed time.

Arguments

x

A matrix containing directional data.

G

The maximum number of clusters to be tested. Default value is 5.

n.start

The number of random starts to try. See also R's built-in function kmeans for more information about this.

Author

Michail Tsagris.

R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Giorgos Athineou <gioathineou@gmail.com>.

Details

If the data are not unit vectors, they are transformed into unit vectors.

References

Hornik, K. and Grun, B. (2014). movMF: An R package for fitting mixtures of von Mises-Fisher distributions. Journal of Statistical Software, 58(10):1--31.

See Also

mixvmf.mle, rmixvmf, mixvmf.contour

Examples

Run this code
x <- as.matrix( iris[, 1:4] )
x <- x / sqrt( rowSums(x^2) )
bic.mixvmf(x)

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