In the current thesis several selected aspects of the two related latent class models; finite mixtures and hidden Markov models, were considered.
The problem of calculating the MLE of a Gaussian mixture with Newton's method and the consistency of penalized MLE were investigated.
A penalized MLE procedure for univariate Gaussian hidden Markov models was introduced and shown to be consistent.
Furthermore, a result on identifiability of nonparametric hidden Markov models is derived.
IdentifikationPoint estimationKonsistenzClassification and discrimination; cluster analysisconsistencySchätzungmaximum likelihoodmaximum likelihoodhidden Markov modelsmixture modelsidentificationhidden Markov ModelleEstimationNone of the above, but in this section
