Dokument
| Titel: | Hidden Markov models: Estimation theory and economic applications |
| Autor: | Leister, Anna Maria |
| Weitere Beteiligte: | Holzmann, Hajo (Prof. Dr.) |
| Veröffentlicht: | 2016 |
| URI: | https://archiv.ub.uni-marburg.de/diss/z2016/0120 |
| URN: | urn:nbn:de:hebis:04-z2016-01208 |
| DOI: | https://doi.org/10.17192/z2016.0120 |
| DDC: | 510 Mathematik |
| Titel (trans.): | Hidden Markov Modelle: Schätztheorie und ökonomische Anwendungen |
| Publikationsdatum: | 2016-05-25 |
| Lizenz: | https://rightsstatements.org/vocab/InC-NC/1.0/ |
| Schlagwörter: |
|---|
| EM-algorithm, Hidden Markov Modell, Schätztheorie, Maximum Likelihood Schätzung, EM-Algorithmus, Statistik, estimation theory, statistics, Hidden Markov models |
Summary:
In this thesis, maximum likelihood estimation of hidden Markov models in several settings is investigated. Nonparametric estimation of state-dependent general mixtures and log-concave densities is discussed theoretically and algorithmically. Penalized estimation for parametric hidden Markov models comparing several penalty functions is studied. In addition, various models based on mixture models and hidden Markov models differing in dependency structure and the inclusion of covariables are applied to a set of panel data containing the GDP of several countries.
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