Calculates the density of observations
x for state
j given the parameters in
model. This is used for
a Poisson emission distribution of a HMM or HSMM and is a suitable prototype for user's to make their own custom distributions.
dpois.hsmm(x, j, model)
This is used by
hsmm to calculate densities for use in the E-step of the EM algorithm.
It can also be used as a template for users wishing to building their own emission distributions
A vector of probability densities.
Jared O'Connell [email protected]
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J<-3 initial <- rep(1/J,J) P <- matrix(c(.8,.5,.1,0.05,.2,.5,.15,.3,.4),nrow=J) b <- list(lambda=c(1,3,6)) model <- hmmspec(init=initial, trans=P, parms.emission=b,dens.emission=dpois.hsmm) model train <- simulate(model, nsim=300, seed=1234, rand.emis=rpois.hsmm) plot(train,xlim=c(0,100)) h1 = hmmfit(train,model,mstep=mstep.pois)
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