Compression-based methods of statistical analysis and prediction of time series

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Compression-based methods of statistical analysis and prediction of time series. / Ryabko, Boris; Astola, Jaakko; Malyutov, Mikhail.

Springer International Publishing, 2016. 144 p.

Research output: Book/Report › Book › Scientific › peer-review

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Ryabko, Boris ; Astola, Jaakko ; Malyutov, Mikhail. / Compression-based methods of statistical analysis and prediction of time series. Springer International Publishing, 2016. 144 p.

Bibtex - Download

@book{1ec1a4e90a2b412fab03cd58576278a8,

title = "Compression-based methods of statistical analysis and prediction of time series",

abstract = "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.",

author = "Boris Ryabko and Jaakko Astola and Mikhail Malyutov",

note = "EXT={"}Ryabko, Boris{"}",

year = "2016",

month = "1",

day = "1",

doi = "10.1007/978-3-319-32253-7",

language = "English",

isbn = "978-3-319-32251-3",

publisher = "Springer International Publishing",

}

RIS (suitable for import to EndNote) - Download

TY - BOOK

T1 - Compression-based methods of statistical analysis and prediction of time series

AU - Ryabko, Boris

AU - Astola, Jaakko

AU - Malyutov, Mikhail

N1 - EXT="Ryabko, Boris"

PY - 2016/1/1

Y1 - 2016/1/1

N2 - 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.

AB - 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.

U2 - 10.1007/978-3-319-32253-7

DO - 10.1007/978-3-319-32253-7

M3 - Book

SN - 978-3-319-32251-3

BT - Compression-based methods of statistical analysis and prediction of time series

PB - Springer International Publishing

ER -

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