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.