| 书目名称 | Introduction to the Statistics of Poisson Processes and Applications | | 编辑 | Yury A. Kutoyants | | 视频video | | | 概述 | Covers an extensive class of models involving inhomogeneous Poisson processes.Discusses various applications.Each chapter concludes with a series of problems | | 丛书名称 | Frontiers in Probability and the Statistical Sciences | | 图书封面 |  | | 描述 | .This book covers an extensive class of models involving inhomogeneous Poisson processes and deals with their identification, i.e. the solution of certain estimation or hypothesis testing problems based on the given dataset. These processes are mathematically easy-to-handle and appear in numerous disciplines, including astronomy, biology, ecology, geology, seismology, medicine, physics, statistical mechanics, economics, image processing, forestry, telecommunications, insurance and finance, reliability, queuing theory, wireless networks, and localisation of sources..Beginning with the definitions and properties of some fundamental notions (stochastic integral, likelihood ratio, limit theorems, etc.), the book goes on to analyse a wide class of estimators for regular and singular statistical models. Special attention is paid to problems of change-point type, and in particular cusp-type change-point models, then the focus turns to the asymptotically efficient nonparametric estimation of the mean function, the intensity function, and of some functionals. Traditional hypothesis testing, including some goodness-of-fit tests, is also discussed. The theory is then applied to three classes | | 出版日期 | Book 2023 | | 关键词 | Poisson Processes; Parameter Estimation; Nonparametric Estimation; Change-point Problems; Misspecificati | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-37054-0 | | isbn_softcover | 978-3-031-37056-4 | | isbn_ebook | 978-3-031-37054-0Series ISSN 2624-9987 Series E-ISSN 2624-9995 | | issn_series | 2624-9987 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 18:16:21
