Compression-Based Methods of Statistical Analysis and Prediction of Time Series
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 importa
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pressionBased Methods of Statistical Analysis and Prediction of Time Series
Compression-Based Methods of Statistical Analysis and Prediction of Time Series
Boris Ryabko • Jaakko Astola • Mikhail Malyutov
Compression-Based Methods of Statistical Analysis and Prediction of Time Series
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Boris Ryabko Inst. of Computational Technologies Siberian Branch of the Russian Academy of Sciences Novosibirsk, Russia
Jaakko Astola Dept. of Signal Processing Tampere University of Technology Tampere, Finland
Mikhail Malyutov Dept. of Mathematics Northeastern University Boston, MA, USA
ISBN 978-3-319-32251-3 DOI 10.1007/978-3-319-32253-7
ISBN 978-3-319-32253-7 (eBook)
Library of Congress Control Number: 2016940381 © Springer International Publishing Switzerland 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG Switzerland
Preface
Initially, in the 1960s, universal codes were developed for lossless data compression in their storing and transmission. Those codes can efficiently compress sequences generated by stationary and ergodic sources with unknown statistics. In the last twenty years, it was realized that universal codes can be used for solving many important problems of prediction and statistical analysis of time series. This book describes recent results in this area. The first chapter of this book is mainly devoted to the application of universal codes to prediction and statistical analysis of time series. The applications of suggested statistical methods to cryptography are quite numerous, so they are described separately in Chap. 2. These two chapters were written by B. Ryabko and J. Astola. The third chapter presents a sketch of the theory behind many applications of a simplified homogeneity test between literary texts based on universal compressors. In particular, this test can be used for authorship attribution if trainin
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