Empirical Likelihood and Quantile Methods for Time Series
Efficiency, Robustness, Optimality, and Prediction
This book integrates the fundamentals of asymptotic theory of statistical inference for time series under nonstandard settings, e.g., infinite variance processes, not only from the point of view of efficiency but also from that of robustness and optimality by minimizing prediction error. This is the first book to consider the generalized empirical likelihood applied to time series models in frequency domain and also the estimation motivated by minimizing quantile prediction error without assumption of true model. It provides the reader with a new horizon for understanding the prediction problem that occurs in time series modeling and a contem…
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Produktdetails
Weitere Autoren: Akashi, Fumiya / Taniguchi, Masanobu
- ISBN: 978-981-10-0151-2
- EAN: 9789811001512
- Produktnummer: 19060991
- Verlag: Springer-Verlag GmbH
- Sprache: Englisch
- Erscheinungsjahr: 2019
- Seitenangabe: 136 S.
- Masse: H23.5 cm x B15.5 cm x D0.8 cm 236 g
- Abbildungen: Book; Bibliographie
- Gewicht: 236
Über den Autor
Yan Liu, Dr., Waseda University, y.liu2@kurenai.waseda.jp, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, JapanFumiya Akashi, Dr., Waseda University, f.akashi@kurenai.waseda.jp, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, JapanMasanobu Taniguchi, Professor, Research Importance Position, Research Institute for Science & Engineering, Waseda University, taniguchi@waseda.jp, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan
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