DEM1 {DEM}

The DEM1 algorithm is a divide and conquer algorithm, which is used to solve the parameter estimation of multivariate Gaussian mixture model.

Description

The DEM1 algorithm is a divide and conquer algorithm, which is used to solve the parameter estimation of multivariate Gaussian mixture model.

Usage

DEM1(y, M, seed, alpha0, mu0, sigma0, i, epsilon)

Arguments

y

is a data matrix

M

is the number of subsets

seed

is the recommended way to specify seeds

alpha0

is the initial value of the mixing weight

mu0

is the initial value of the mean

sigma0

is the initial value of the covariance

i

is the number of iterations

epsilon

is the threshold value

Value

DEM1alpha,DEM1mu,DEM1sigma,DEM1time

Examples

library(mvtnorm)
alpha1= c(rep(1/4,4)) 
mu1=matrix(0,nrow=4,ncol=4) 
for (k in 1:4){
mu1[4,]=c(runif(4,(k-1)*3,k*3)) 
}
sigma1=list()
for (k in 1:4){
sigma1[[k]]= diag(4)*0.1
}
y= matrix(0,nrow=200,ncol=4) 
for(k in 1:4){
y[c(((k-1)*200/4+1):(k*200/4)),] = rmvnorm(200/4,mu1[k,],sigma1[[k]]) 
}
M=5
seed=123
alpha0= alpha1
mu0=mu1
sigma0=sigma1
i=10
epsilon=0.005
DEM1(y,M,seed,alpha0,mu0,sigma0,i,epsilon)