mixmvnorm_mstep function

the M step function of the EM algorithm

The M step function of the EM algorithm for the mixture of multivariate normals as the emission distribution using the observation matrix and the estimated weight vectors

mixmvnorm_mstep(x, wt1, wt2)

Arguments

• x: the observation matrix
• wt1: the state probabilities matrix (number of observations times number of states)
• wt2: the mixture components probabilities list (of length nstate) of matrices (number of observations times number of mixture components)

Returns

list of emission (mixture multivariate normal) parameters: (mu, sigma and mix.p)

Examples

data(CMAPSS)
n = nrow(CMAPSS$train$x)
wt1 = matrix(runif(3*n),nrow=n,ncol=3)
wt2 = list()
for(j in 1:3) wt2[[j]] = matrix(runif(5*n),nrow=n,ncol=5)
emission = mixmvnorm_mstep(CMAPSS$train$x, wt1, wt2)

Author(s)

Morteza Amini, morteza.amini@ut.ac.ir , Afarin Bayat, aftbayat@gmail.com