Directional (version 6.8)

Contour plot (on the sphere) of a mixture of von Mises-Fisher distributions: Contour plot (on the sphere) of a mixture of von Mises-Fisher distributions

Description

The contour plot (on the sphere) of a mixture of von Mises-Fisher distributions is produced.

Usage

spher.mixvmf.contour(probs, mu, k, bgcol = "snow", dat = NULL, col = NULL,
lat = 50, long = 50)

Value

A plot containing the contours of the mixture distribution.

Arguments

probs

This is avector with the mixing probability of each group.

mu

A matrix with the mean direction of each group.

k

A vector with the concentration parameter of each group.

bgcol

The color of the surface of the sphere.

dat

If you have you want to plot supply them here. This has to be a numerical matrix with three columns, i.e. unit vectors.

col

If you supplied data then choose the color of the points. If you did not choose a color, the points will appear in red.

lat

A positive number determing the range of degrees to move left and right from the latitude center. See the example to better understand this argument.

long

A positive number determing the range of degrees to move up and down from the longitude center. See the example to better understand this argument.

Author

Michail Tsagris.

R implementation and documentation: Michail Tsagris .

Details

The goal of this function is for the user to see how the mixtures of von Mises-Fisher look like.

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

Mardia K. V. and Jupp, P. E. (2000). Directional statistics. Chicester: John Wiley & Sons.

Sra S. (2012). A short note on parameter approximation for von Mises-Fisher distributions: and a fast implementation of \(I_s(x)\). Computational Statistics, 27(1): 177--190.

See Also

spher.esag.contour, spher.vmf.contour, mixvmf.mle

Examples

# \donttest{
k <- runif(3, 4, 20)
probs <- c(0.2, 0.5, 0.3)
mu <- matrix(rnorm(9, 0, 0.5), ncol = 3)
mu <- mu / sqrt( rowSums(mu^2) )
## the lat and long are decreased to 10. Increase them back to 50 to
## see the difference
spher.mixvmf.contour(probs, mu, k, lat = 10, long = 10)
# }