Compression-Based Methods of Statistical Analysis and Prediction of Time Series

Author:   Boris Ryabko ,  Jaakko Astola ,  Mikhail Malyutov
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2016
ISBN:  

9783319322513


Pages:   144
Publication Date:   27 May 2016
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Compression-Based Methods of Statistical Analysis and Prediction of Time Series


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Overview

Universal codes efficiently compress sequences generated by stationary and ergodic sources with unknown statistics, and they were originally designed for lossless data compression. In the meantime, it was realized that they can be used for solving important problems of prediction and statistical analysis of time series, and this book describes recent results in this area. The first chapter introduces and describes the application of universal codes to prediction and the statistical analysis of time series; the second chapter describes applications of selected statistical methods to cryptography, including attacks on block ciphers; and the third chapter describes a homogeneity test used to determine authorship of literary texts. The book will be useful for researchers and advanced students in information theory, mathematical statistics, time-series analysis, and cryptography. It is assumed that the reader has some grounding in statistics and in information theory.

Full Product Details

Author:   Boris Ryabko ,  Jaakko Astola ,  Mikhail Malyutov
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2016
Dimensions:   Width: 15.50cm , Height: 1.10cm , Length: 23.50cm
Weight:   3.613kg
ISBN:  

9783319322513


ISBN 10:   3319322516
Pages:   144
Publication Date:   27 May 2016
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Reviews

The book under review describes several recent results on Universal Codes. ... its reading may be useful for non-mathematical professionals interested in handling large data sources. (Oscar Bustos, zbMATH 1360.94001, 2017)


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