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Time Series with Long Memory comprises a collection on time series analysis. Long memory time series are characterized by a strong dependence between distant events. Various methods and their theoretical properties are discussed with empirical applications. The methods constitute a very flexible approach to analyzing time series data arising in economics, finance and other fields.About the SeriesAdvanced Texts in Econometrics is a distinguished and rapidly expanding series in which leading econometricians assess recent developments in such areas as stochastic probability, panel and time series data analysis, modeling, and cointegration. In both hardback and affordable paperback, each volume explains the nature and applicability of a topic in greater depth than possible in introductory textbooks or single journal articles. Each definitive work is formatted to be as accessible and convenient for those who are not familiar with the detailed primary literature.
This text investigates the theoretical properties and practical applications of time series models characterized by long memory, where distant observations exhibit strong dependence. Peter M. Robinson, a prominent econometrician, synthesizes complex statistical frameworks to provide a rigorous analysis of these processes. The book serves as a comprehensive resource for researchers and students, bridging the gap between primary literature and applied econometric modeling in fields such as finance and economics.
What You Will Find
Experts recognize this volume as a foundational text within the Advanced Texts in Econometrics series, valued for its depth and technical precision. Readers frequently note the academic density of the prose, which is intended for those with a solid background in statistical theory.
Page Count:
392
Publication Date:
2003-08-28
Publisher:
Oxford University Press
ISBN-10:
0199257302
ISBN-13:
9780199257300
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