Time Series Analysis with Long Memory in View (Wiley Series in Probability and Statistics) - Hardcover

Hassler, Uwe

Hardcover

ISBN 10: 1119470404 ISBN 13: 9781119470403

Publisher: Wiley, 2019

Synopsis

Provides a simple exposition of the basic time series material, and insights into underlying technical aspects and methods of proof 

Long memory time series are characterized by a strong dependence between distant events. This book introduces readers to the theory and foundations of univariate time series analysis with a focus on long memory and fractional integration, which are embedded into the general framework. It presents the general theory of time series, including some issues that are not treated in other books on time series, such as ergodicity, persistence versus memory, asymptotic properties of the periodogram, and Whittle estimation.  Further chapters address the general functional central limit theory, parametric and semiparametric estimation of the long memory parameter, and locally optimal tests.

Intuitive and easy to read, Time Series Analysis with Long Memory in View offers chapters that cover: Stationary Processes; Moving Averages and Linear Processes; Frequency Domain Analysis; Differencing and Integration; Fractionally Integrated Processes; Sample Means; Parametric Estimators; Semiparametric Estimators; and Testing. It also discusses further topics. This book: 

• Offers beginning-of-chapter examples as well as end-of-chapter technical arguments and proofs
• Contains many new results on long memory processes which have not appeared in previous and existing textbooks
• Takes a basic mathematics (Calculus) approach to the topic of time series analysis with long memory
• Contains 25 illustrative figures as well as lists of notations and acronyms

Time Series Analysis with Long Memory in View is an ideal text for first year PhD students, researchers, and practitioners in statistics, econometrics, and any application area that uses time series over a long period. It would also benefit researchers, undergraduates, and practitioners in those areas who require a rigorous introduction to time series analysis.

About this title

About the Author

UWE HASSLER, PHD, is full professor of statistics and econometric methods, Goethe University, Frankfurt. He is also associate editor of Advances in Statistical Analysis. He received his PhD from FU Berlin in 1993 and is recipient of the Opus magnum grant from VolkswagenStiftung.

From the Back Cover

PROVIDES A SIMPLE EXPOSITION OF THE BASIC TIME SERIES MATERIAL, AND INSIGHTS INTO UNDERLYING TECHNICAL ASPECTS AND METHODS OF PROOF

Long memory time series are characterized by a strong dependence between distant events. This book introduces readers to the theory and foundations of univariate time series analysis with a focus on long memory and fractional integration, which are embedded into the general framework. It presents the general theory of time series, including some issues that are not treated in other books on time series, such as ergodicity, persistence versus memory, asymptotic properties of the periodogram, and Whittle estimation. Further chapters address the general functional central limit theory, parametric and semiparametric estimation of the long memory parameter, and locally optimal tests.

Intuitive and easy to read, Time Series Analysis with Long Memory in View offers chapters that cover: Stationary Processes; Moving Averages and Linear Processes; Frequency Domain Analysis; Differencing and Integration; Fractionally Integrated Processes; Sample Means; Parametric Estimators; Semiparametric Estimators; and Testing. It also discusses further topics. This book:

• Offers beginning-of-chapter examples as well as end-of-chapter technical arguments and proofs
• Contains many new results on long memory processes which have not appeared in previous and existing textbooks
• Takes a basic mathematics (Calculus) approach to the topic of time series analysis with long memory
• Contains 25 illustrative figures as well as lists of notations and acronyms

Time Series Analysis with Long Memory in View is an ideal text for first year PhD students, researchers, and practitioners in statistics, econometrics, and any application area that uses time series over a long period. It would also benefit researchers, undergraduates, and practitioners in those areas who require a rigorous introduction to time series analysis.

From the Inside Flap

PROVIDES A SIMPLE EXPOSITION OF THE BASIC TIME SERIES MATERIAL, AND INSIGHTS INTO UNDERLYING TECHNICAL ASPECTS AND METHODS OF PROOF

Long memory time series are characterized by a strong dependence between distant events. This book introduces readers to the theory and foundations of univariate time series analysis with a focus on long memory and fractional integration, which are embedded into the general framework. It presents the general theory of time series, including some issues that are not treated in other books on time series, such as ergodicity, persistence versus memory, asymptotic properties of the periodogram, and Whittle estimation. Further chapters address the general functional central limit theory, parametric and semiparametric estimation of the long memory parameter, and locally optimal tests.

Intuitive and easy to read, Time Series Analysis with Long Memory in View offers chapters that cover: Stationary Processes; Moving Averages and Linear Processes; Frequency Domain Analysis; Differencing and Integration; Fractionally Integrated Processes; Sample Means; Parametric Estimators; Semiparametric Estimators; and Testing. It also discusses further topics. This book:

• Offers beginning-of-chapter examples as well as end-of-chapter technical arguments and proofs
• Contains many new results on long memory processes which have not appeared in previous and existing textbooks
• Takes a basic mathematics (Calculus) approach to the topic of time series analysis with long memory
• Contains 25 illustrative figures as well as lists of notations and acronyms

Time Series Analysis with Long Memory in View is an ideal text for first year PhD students, researchers, and practitioners in statistics, econometrics, and any application area that uses time series over a long period. It would also benefit researchers, undergraduates, and practitioners in those areas who require a rigorous introduction to time series analysis.

Edition details

• Publisher: Wiley
• Publication date: 2019
• Language: English
• ISBN 10: 1119470404
• ISBN 13: 9781119470403
• Binding: Hardcover
• Edition number: 1
• Number of pages: 288