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Mixing : Properties and Examples / by Paul Doukhan
(Lecture Notes in Statistics. ISSN:21977186 ; 85)

1st ed. 1994.
出版者 (New York, NY : Springer New York : Imprint: Springer)
出版年 1994
大きさ XII, 142 p. 5 illus : online resource
著者標目 *Doukhan, Paul author
SpringerLink (Online service)
件 名 LCSH:Mathematics
FREE:Applications of Mathematics
一般注記 1. General properties -- 1.1. Dependence of ?-fields -- 1.2. Basic tools -- 1.3. Mixing -- 1.4. Tools -- 1.5. Central limit theorem -- 2. Examples -- 2.1. Gaussian random fields -- 2.2. Gibbs fields -- 2.3. Linear fields -- 2.4. Markov processes -- 2.5. Continuous time processes
Mixing is concerned with the analysis of dependence between sigma-fields defined on the same underlying probability space. It provides an important tool of analysis for random fields, Markov processes, central limit theorems as well as being a topic of current research interest in its own right. The aim of this monograph is to provide a study of applications of dependence in probability and statistics. It is divided in two parts, the first covering the definitions and probabilistic properties of mixing theory. The second part describes mixing properties of classical processes and random fields as well as providing a detailed study of linear and Gaussian fields. Consequently, this book will provide statisticians dealing with problems involving weak dependence properties with a powerful tool
HTTP:URL=https://doi.org/10.1007/978-1-4612-2642-0
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書誌ID 4000105527
ISBN 9781461226420

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