Periodically Correlated Random Sequences: Spectral Theory and Practice (Wiley Series in Probability and Statistics)

Hurd, Harry L.; Miamee, Abolghassem

Published by Wiley-Interscience
ISBN 10: 047134771X / ISBN 13: 9780471347712
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Synopsis: Uniquely combining theory, application, and computing, this book explores the spectral approach to time series analysis

The use of periodically correlated (or cyclostationary) processes has become increasingly popular in a range of research areas such as meteorology, climate, communications, economics, and machine diagnostics. Periodically Correlated Random Sequences presents the main ideas of these processes through the use of basic definitions along with motivating, insightful, and illustrative examples. Extensive coverage of key concepts is provided, including second-order theory, Hilbert spaces, Fourier theory, and the spectral theory of harmonizable sequences. The authors also provide a paradigm for nonparametric time series analysis including tests for the presence of PC structures.

Features of the book include:

  • An emphasis on the link between the spectral theory of unitary operators and the correlation structure of PC sequences

  • A discussion of the issues relating to nonparametric time series analysis for PC sequences, including estimation of the mean, correlation, and spectrum

  • A balanced blend of historical background with modern application-specific references to periodically correlated processes

  • An accompanying Web site that features additional exercises as well as data sets and programs written in MATLAB® for performing time series analysis on data that may have a PC structure

Periodically Correlated Random Sequences is an ideal text on time series analysis for graduate-level statistics and engineering students who have previous experience in second-order stochastic processes (Hilbert space), vector spaces, random processes, and probability. This book also serves as a valuable reference for research statisticians and practitioners in areas of probability and statistics such as time series analysis, stochastic processes, and prediction theory.

About the Author:

Harry L. Hurd, PhD, is Adjunct Professor of Statistics at The University of North Carolina at Chapel Hill. He is the founder of Hurd Associates, Inc., a research and development firm concentrating in the areas of signal processing and stochastic processes. Dr. Hurd has published extensively on the topics of nonstationary random processes, periodically correlated processes, and nonparametric time series.

Abolghassem Miamee, PhD, is Professor of Mathematics at Hampton University in Virginia. His research interests include stochastic processes, time series analysis, and harmonic and functional analysis.

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Title: Periodically Correlated Random Sequences: ...
Publisher: Wiley-Interscience
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Book Description John Wiley and Sons Ltd, United Kingdom, 2007. Hardback. Book Condition: New. Language: English . Brand New Book. Uniquely combining theory, application, and computing, this book explores the spectral approach to time series analysis The use of periodically correlated (or cyclostationary) processes has become increasingly popular in a range of research areas such as meteorology, climate, communications, economics, and machine diagnostics. Periodically Correlated Random Sequences presents the main ideas of these processes through the use of basic definitions along with motivating, insightful, and illustrative examples. Extensive coverage of key concepts is provided, including second-order theory, Hilbert spaces, Fourier theory, and the spectral theory of harmonizable sequences. The authors also provide a paradigm for nonparametric time series analysis including tests for the presence of PC structures. Features of the book include:* An emphasis on the link between the spectral theory of unitary operators and the correlation structure of PC sequences* A discussion of the issues relating to nonparametric time series analysis for PC sequences, including estimation of the mean, correlation, and spectrum* A balanced blend of historical background with modern application-specific references to periodically correlated processes* An accompanying Web site that features additional exercises as well as data sets and programs written in MATLAB(r) for performing time series analysis on data that may have a PC structure Periodically Correlated Random Sequences is an ideal text on time series analysis for graduate-level statistics and engineering students who have previous experience in second-order stochastic processes (Hilbert space), vector spaces, random processes, and probability. This book also serves as a valuable reference for research statisticians and practitioners in areas of probability and statistics such as time series analysis, stochastic processes, and prediction theory. Bookseller Inventory # AAH9780471347712

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Book Description John Wiley and Sons Ltd, United Kingdom, 2007. Hardback. Book Condition: New. Language: English . Brand New Book. Uniquely combining theory, application, and computing, this book explores the spectral approach to time series analysis The use of periodically correlated (or cyclostationary) processes has become increasingly popular in a range of research areas such as meteorology, climate, communications, economics, and machine diagnostics. Periodically Correlated Random Sequences presents the main ideas of these processes through the use of basic definitions along with motivating, insightful, and illustrative examples. Extensive coverage of key concepts is provided, including second-order theory, Hilbert spaces, Fourier theory, and the spectral theory of harmonizable sequences. The authors also provide a paradigm for nonparametric time series analysis including tests for the presence of PC structures. Features of the book include: An emphasis on the link between the spectral theory of unitary operators and the correlation structure of PC sequences A discussion of the issues relating to nonparametric time series analysis for PC sequences, including estimation of the mean, correlation, and spectrum A balanced blend of historical background with modern application-specific references to periodically correlated processes An accompanying Web site that features additional exercises as well as data sets and programs written in MATLAB (R) for performing time series analysis on data that may have a PC structure Periodically Correlated Random Sequences is an ideal text on time series analysis for graduate-level statistics and engineering students who have previous experience in second-order stochastic processes (Hilbert space), vector spaces, random processes, and probability. This book also serves as a valuable reference for research statisticians and practitioners in areas of probability and statistics such as time series analysis, stochastic processes, and prediction theory. Bookseller Inventory # AAH9780471347712

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