| 书目名称 | Weak Convergence and Empirical Processes | | 副标题 | With Applications to | | 编辑 | Aad W. Vaart,Jon A. Wellner | | 视频video | | | 丛书名称 | Springer Series in Statistics | | 图书封面 |  | | 描述 | This book tries to do three things. The first goal is to give an exposition of certain modes of stochastic convergence, in particular convergence in distribution. The classical theory of this subject was developed mostly in the 1950s and is well summarized in Billingsley (1968). During the last 15 years, the need for a more general theory allowing random elements that are not Borel measurable has become well established, particularly in developing the theory of empirical processes. Part 1 of the book, Stochastic Convergence, gives an exposition of such a theory following the ideas of J. Hoffmann-J!1Jrgensen and R. M. Dudley. A second goal is to use the weak convergence theory background devel oped in Part 1 to present an account of major components of the modern theory of empirical processes indexed by classes of sets and functions. The weak convergence theory developed in Part 1 is important for this, simply because the empirical processes studied in Part 2, Empirical Processes, arenaturally viewed as taking values in nonseparable Banach spaces, even in the most elementary cases, and are typically not Borel measurable. Much of the theory presented in Part 2 has previously been sc | | 出版日期 | Book 19961st edition | | 关键词 | Estimator; Mathematics; Maxima; Maximum; Minimum; Random variable; Statistics | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4757-2545-2 | | isbn_softcover | 978-1-4757-2547-6 | | isbn_ebook | 978-1-4757-2545-2Series ISSN 0172-7397 Series E-ISSN 2197-568X | | issn_series | 0172-7397 | | copyright | Springer Science+Business Media New York 1996 |
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发表于 2025-3-21 19:56:11
