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Titel:Inference and Application of Likelihood Based Methods for Hidden Markov Models
Autor:Schwaiger, Florian
Weitere Beteiligte: Holzmann, Hajo (Prof. Dr.)
Veröffentlicht:2013
URI:https://archiv.ub.uni-marburg.de/diss/z2013/0416
DOI: https://doi.org/10.17192/z2013.0416
URN: urn:nbn:de:hebis:04-z2013-04165
DDC:510 Mathematik
Titel (trans.):Inferenz und Anwendung Likelihood-basierter Methoden für Hidden Markov Modelle
Publikationsdatum:2013-09-17
Lizenz:https://rightsstatements.org/vocab/InC-NC/1.0/

Dokument

Schlagwörter:
hidden Markov model, Hidden-Markov-Modell, Likelihood-ratio test, Likelihood-Quotienten-Test

Summary:
The thesis consists of three papers. In the paper “Testing for the number of states in hidden Markov models” we generalize existing testing procedures for i.i.d. mixture models to hidden Markov models by considering penalized quasi-likelihood ratio tests. They can be applied in order to assess the number of states k of a hidden Markov model with univariate state-dependent distribution fulfilling certain regularity conditions. In the paper “Hidden Markov Models with state-dependent mixtures” we analyze the dependence structure of hidden Markov models with state-dependent finite mixtures. Our results have applications to model selection as well as to model-based clustering. We propose algorithms for both purposes. In the paper “Peaks vs Components” we analyze welfare groups of countries all over the world by applying finite mixture models to the GDP per capita of 190 countries from 1970 to 2009.

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