| 書目名稱 | Weighted Empirical Processes in Dynamic Nonlinear Models |
| 編輯 | Hira L. Koul |
| 視頻video | http://file.papertrans.cn/1022/1021968/1021968.mp4 |
| 叢書名稱 | Lecture Notes in Statistics |
| 圖書封面 |  |
| 描述 | The role of the weak convergence technique via weighted empirical processes has proved to be very useful in advancing the development of the asymptotic theory of the so called robust inference procedures corresponding to non-smooth score functions from linear models to nonlinear dynamic models in the 1990‘s. This monograph is an ex- panded version of the monograph Weighted Empiricals and Linear Models, IMS Lecture Notes-Monograph, 21 published in 1992, that includes some aspects of this development. The new inclusions are as follows. Theorems 2. 2. 4 and 2. 2. 5 give an extension of the Theorem 2. 2. 3 (old Theorem 2. 2b. 1) to the unbounded random weights case. These results are found useful in Chapters 7 and 8 when dealing with ho- moscedastic and conditionally heteroscedastic autoregressive models, actively researched family of dynamic models in time series analysis in the 1990‘s. The weak convergence results pertaining to the partial sum process given in Theorems 2. 2. 6 . and 2. 2. 7 are found useful in fitting a parametric autoregressive model as is expounded in Section 7. 7 in some detail. Section 6. 6 discusses the related problem of fit- ting a regression model, using a ce |
| 出版日期 | Book 2002Latest edition |
| 關鍵詞 | boundary element method; estimator; fitting; probability; statistics |
| 版次 | 2 |
| doi | https://doi.org/10.1007/978-1-4613-0055-7 |
| isbn_softcover | 978-0-387-95476-9 |
| isbn_ebook | 978-1-4613-0055-7Series ISSN 0930-0325 Series E-ISSN 2197-7186 |
| issn_series | 0930-0325 |
| copyright | Springer Science+Business Media New York 2002 |
|Archiver|手機版|小黑屋|
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