BIC for the model based clustering using mixtures of von Mises-Fisher distributions {Directional}

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)

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.

Details

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

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.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail] and Giorgos Athineou <[e-mail]>.

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

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