| 书目名称 | Exponential Families of Stochastic Processes |
| 编辑 | Uwe Küchler,Michael Sørensen |
| 视频video | |
| 概述 | The first book to cover exponential families of stochastic processes *.The statistical concepts are explained carefully so that probabilists with only a basic background in statistics can use the book |
| 丛书名称 | Springer Series in Statistics |
| 图书封面 |  |
| 描述 | Exponential families of stochastic processes are parametric stochastic p- cess models for which the likelihood function exists at all ?nite times and has an exponential representation where the dimension of the canonical statistic is ?nite and independent of time. This de?nition not only covers manypracticallyimportantstochasticprocessmodels,italsogivesrisetoa rather rich theory. This book aims at showing both aspects of exponential families of stochastic processes. Exponential families of stochastic processes are tractable from an a- lytical as well as a probabilistic point of view. Therefore, and because the theory covers many important models, they form a good starting point for an investigation of the statistics of stochastic processes and cast interesting light on basic inference problems for stochastic processes. Exponential models play a central role in classical statistical theory for independent observations, where it has often turned out to be informative and advantageous to view statistical problems from the general perspective of exponential families rather than studying individually speci?c expon- tial families of probability distributions. The same is true of stochast |
| 出版日期 | Book 1997 |
| 关键词 | Likelihood; Markov process; Martingale; Semimartingale; Stochastic calculus; Stochastic processes; statist |
| 版次 | 1 |
| doi | https://doi.org/10.1007/b98954 |
| isbn_softcover | 978-1-4757-7100-8 |
| isbn_ebook | 978-0-387-22765-8Series ISSN 0172-7397 Series E-ISSN 2197-568X |
| issn_series | 0172-7397 |
| copyright | Springer Science+Business Media New York 1997 |
发表于 2025-3-21 18:21:24
