Long-Memory Processes

Probabilistic Properties and Statistical Methods

Business & Finance, Economics, Statistics, Nonfiction, Science & Nature, Mathematics
Cover of the book Long-Memory Processes by Jan Beran, Sucharita Ghosh, Rafal Kulik, Yuanhua Feng, Springer Berlin Heidelberg
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Author: Jan Beran, Sucharita Ghosh, Rafal Kulik, Yuanhua Feng ISBN: 9783642355127
Publisher: Springer Berlin Heidelberg Publication: May 14, 2013
Imprint: Springer Language: English
Author: Jan Beran, Sucharita Ghosh, Rafal Kulik, Yuanhua Feng
ISBN: 9783642355127
Publisher: Springer Berlin Heidelberg
Publication: May 14, 2013
Imprint: Springer
Language: English

Long-memory processes are known to play an important part in many areas of science and technology, including physics, geophysics, hydrology, telecommunications, economics, finance, climatology, and network engineering. In the last 20 years enormous progress has been made in understanding the probabilistic foundations and statistical principles of such processes. This book provides a timely and comprehensive review, including a thorough discussion of mathematical and probabilistic foundations and statistical methods, emphasizing their practical motivation and mathematical justification. Proofs of the main theorems are provided and data examples illustrate practical aspects. This book will be a valuable resource for researchers and graduate students in statistics, mathematics, econometrics and other quantitative areas, as well as for practitioners and applied researchers who need to analyze data in which long memory, power laws, self-similar scaling or fractal properties are relevant.

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Long-memory processes are known to play an important part in many areas of science and technology, including physics, geophysics, hydrology, telecommunications, economics, finance, climatology, and network engineering. In the last 20 years enormous progress has been made in understanding the probabilistic foundations and statistical principles of such processes. This book provides a timely and comprehensive review, including a thorough discussion of mathematical and probabilistic foundations and statistical methods, emphasizing their practical motivation and mathematical justification. Proofs of the main theorems are provided and data examples illustrate practical aspects. This book will be a valuable resource for researchers and graduate students in statistics, mathematics, econometrics and other quantitative areas, as well as for practitioners and applied researchers who need to analyze data in which long memory, power laws, self-similar scaling or fractal properties are relevant.

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