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Titlebook: Exponential Families of Stochastic Processes; Uwe Küchler,Michael S?rensen Book 1997 Springer Science+Business Media New York 1997 Likelih

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書目名稱Exponential Families of Stochastic Processes
編輯Uwe Küchler,Michael S?rensen
視頻videohttp://file.papertrans.cn/320/319712/319712.mp4
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
叢書名稱Springer Series in Statistics
圖書封面Titlebook: Exponential Families of Stochastic Processes;  Uwe Küchler,Michael S?rensen Book 1997 Springer Science+Business Media New York 1997 Likelih
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
關(guān)鍵詞Likelihood; Markov process; Martingale; Semimartingale; Stochastic calculus; Stochastic processes; statist
版次1
doihttps://doi.org/10.1007/b98954
isbn_softcover978-1-4757-7100-8
isbn_ebook978-0-387-22765-8Series ISSN 0172-7397 Series E-ISSN 2197-568X
issn_series 0172-7397
copyrightSpringer Science+Business Media New York 1997
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Book 1997y 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
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