Directional (version 4.0)

Mixtures of Von Mises-Fisher distributions: Mixtures of Von Mises-Fisher distributions

Description

It performs model based clustering for circualr, spherical and hyperspherical data assuming von Mises-Fisher distributions.

Usage

mix.vmf(x, g ,n.start = 20)

Arguments

x

A matrix with the data expressed as unit vectors.

g

The number of groups to fit. It must be greater than or equal to 2.

n.start

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

Value

A list including:

param

A matrix with the mean direction, the concetrations parameter and mixing probability of each group.

loglik

The value of the maximised log-likelihood.

pred

The predicted group of each observation.

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.

Details

The initial step of the algorithm is not based on a spherical k-means, but on s imple k-means. The results are comparable to the package movMF.

References

Kurt Hornik and Bettina Grun (2014). movMF: An R Package for Fitting Mixtures of von Mises-Fisher Distributions http://cran.r-project.org/web/packages/movMF/vignettes/movMF.pdf

See Also

rmixvmf, bic.mixvmf, mixvmf.contour

Examples

# NOT RUN {
k <- runif(4, 4, 20)
prob <- c(0.2, 0.4, 0.3, 0.1)
mu <- matrix(rnorm(16), ncol = 4)
mu <- mu / sqrt( rowSums(mu^2) )
x <- rmixvmf(200, prob, mu, k)$x
mix.vmf(x, 3)
mix.vmf(x, 4)
mix.vmf(x, 5)
# }