gen_K {Kmedians}

gen_K

Description

Generate a sample of a Gaussian Mixture Model whose centers are generate randomly on a sphere of radius radius.

Usage

gen_K(n=500,d=5,K=3,pcont=0,df=1,
      cont="Student",min=-5,max=5,radius=5)

Arguments

n

A positive integer giving the number of data per cluster. Default is 500.

d

A positive integer giving the dimension. Default is 5.

K

A positive integer giving the number of clusters. Default is 3.

pcont

A scalar between 0 and 1 giving the proportion of contaminated data.

df

A positive integer giving the degrees of freedom of the law of the contaminated data if cont='Student'. Default is 1.

cont

The law of the contaminated data. Can be 'Student' (default) and 'Unif'.

min

A scalar giving the lower bound of the uniform law if cont='Unif'. Default is -5.

max

A scalar giving the upper bound of the uniform law if cont='Unif'. Default is 5.

radius

The radius of the sphere on each the centers of the class are generated. Default is 5.

Value

A list with:

X

A numerical matrix giving the generated data.

cluster

An character vector specifying the true classification.

See Also

See also Kmedians and Kmeans.

Examples

n <- 500
K <- 3
pcont <- 0.2
ech <- gen_K(n=n,K=K,pcont=pcont)
X=ech$X