| 書目名稱 | Empirical Likelihood and Quantile Methods for Time Series |
| 副標(biāo)題 | Efficiency, Robustne |
| 編輯 | Yan Liu,Fumiya Akashi,Masanobu Taniguchi |
| 視頻video | http://file.papertrans.cn/309/308865/308865.mp4 |
| 概述 | Deals with nonstandard settings such as infinite variance rather than weakly stationary time series.Demonstrates that methods for parameter estimation and hypotheses testing are essentially nonparamet |
| 叢書名稱 | SpringerBriefs in Statistics |
| 圖書封面 |  |
| 描述 | 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 contemporary approach of hypothesis testing by the generalized empirical likelihood method. Nonparametric aspects of the methods proposed in this book also satisfactorily address economic and financial problems without imposing redundantly strong restrictions on the model, which has been true until now. Dealing with infinite variance processes makesanalysis of economic and financial data more accurate under the existing results from the demonstrative research. The scope of applications, however, is expected to apply to much broader academic fields. T |
| 出版日期 | Book 2018 |
| 關(guān)鍵詞 | Empirical Likelihood; Quantile Score; Heavy Tail; Efficiency; Robustness |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-981-10-0152-9 |
| isbn_softcover | 978-981-10-0151-2 |
| isbn_ebook | 978-981-10-0152-9Series ISSN 2191-544X Series E-ISSN 2191-5458 |
| issn_series | 2191-544X |
| copyright | The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2018 |
|Archiver|手機(jī)版|小黑屋|
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