search for: m_step

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2007 May 11
0
EM covergence problem
...(D==0,log(p1),log(p2)) } return (probs) } #H [individuals][class] E_step = function(alpha,Beta){#calc posterior of H tmpH = matrix(,nrow = 1000,ncol =3) lprobs = logProbInd(Beta) for(i in 1:3){#classes tmpH[,i] = alpha[i]*exp(lprobs[,i]) } H = tmpH /apply(tmpH,1,sum) return( H) } M_step = function(H,Beta){ #first part use direct estimation aita = apply(H,2,sum)/1000 opt.c = optim(Beta,Q2,H=H,method="BFGS",control = list(fnscale = -1)) lik = opt.c$value return(c(aita,opt.c$par,lik)) } #EM loops alf = c(0.33,0.33,0.33) Bt = seq(0.1,0.6,by=0.1) sc = rep(-8000,5)...