Re-estimates the parameters of a multivariate normal emission
distribution as part of the EM algorithm for HMMs and HSMMs.
This is called by the
hsmm functions. It is a
suitable prototype function for users wishing to design their own
A vector of observed values
A T x J matrix of weights. Column entries are the weights for respective states.
Users may write functions that take the same arguments and return the same values for their own custom emission distributions.
emission slot of a
A list of length J contain the mean vectors
A list of length J containing the covariance matrices
Jared O'Connell [email protected]
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J<-2 initial <- rep(1/J,J) P <- matrix(c(.3,.5,.7,.5),nrow=J) b <- list(mu=list(c(-3,0),c(1,2)),sigma=list(diag(2),matrix(c(4,2,2,3), ncol=2))) model <- hmmspec(init=initial, trans=P, parms.emission=b,dens.emission=dmvnorm.hsmm) model train <- simulate(model, nsim=300, seed=1234, rand.emis=rmvnorm.hsmm) plot(train,xlim=c(0,100)) h1 = hmmfit(train,model,mstep=mstep.mvnorm)
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