Nothing
Mstep.nh.MSAR.VM <-
function(data,theta,FB,covar.trans=NULL,method=method,constr=0) {
order=attributes(theta)$order
d=dim(data)[3]
if(is.na(d) | is.null(d)){d=1}
M=attributes(theta)$NbRegimes
if (length(covar.trans)==1) {
Lag = covar.trans
covar.trans = array(data[(1):(T-Lag+1),,],c(T-Lag+1,N.samples,d))
data = array(data[Lag:T,,],c(T-Lag+1,N.samples,d))
}
N.samples = dim(covar.trans)[2]
ncov.trans = dim(covar.trans)[3]
par.hh = Mstep.hh.MSAR.VM(data,theta,FB,constr)
theta$transmat[which(theta$transmat<1e-15)] = 1e-15
theta$transmat = mk_stochastic(theta$transmat)
trans = para_trans(theta$transmat)
par.trans = theta$par.trans
nh_transition = attributes(theta)$nh.transitions
#par.init = plie2(trans,par.trans)
par.init = plie2.VM(trans,par.trans)
lxi = dim(FB$probSS)[3]
if (order>0) {deb = order+1}
else {deb = 1}
resopt = ucminf(par.init,fn=loglik_nh_inp.VM,gr=NULL,covar=array(covar.trans[deb+(1:(lxi)),,],c(lxi,N.samples,ncov.trans)),xi=FB$probSS,nh_transition=nh_transition,hessian=0,control = list(trace=FALSE))
#res = deplie2(resopt$par);
res = deplie2.VM(resopt$par);
trans = res$trans ;
par.trans = res$par ;
transmat=para_trans_inv(trans);
list(mu=par.hh$mu,kappa = par.hh$kappa,prior=par.hh$prior,transmat=transmat,par.trans=par.trans)
}
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