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＜電子ブック＞
Mixing : Properties and Examples / by Paul Doukhan
(Lecture Notes in Statistics. ISSN:21977186 ; 85)

版	1st ed. 1994.
出版者	New York, NY : Springer New York : Imprint: Springer
出版年	1994
本文言語	英語
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 Accessibility summary: This PDF is not accessible. It is based on scanned pages and does not support features such as screen reader compatibility or described non-text content (images, graphs etc). However, it likely supports searchable and selectable text based on OCR (Optical Character Recognition). Users with accessibility needs may not be able to use this content effectively. Please contact us at accessibilitysupport@springernature.com if you require assistance or an alternative format Inaccessible, or known limited accessibility No reading system accessibility options actively disabled Publisher contact for further accessibility information: accessibilitysupport@springernature.com HTTP:URL=https://doi.org/10.1007/978-1-4612-2642-0

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