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Hidden Markov models: Estimation theory and economic applications
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 c...
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| Định dạng: | Dissertation |
| Ngôn ngữ: | Tiếng Anh |
| Được phát hành: |
Philipps-Universität Marburg
2016
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| Những chủ đề: | |
| Truy cập trực tuyến: | Bài toàn văn PDF |
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| Tóm tắt: | 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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| Mô tả vật lý: | 126 Seiten |
| DOI: | 10.17192/z2016.0120 |