„... Palma presents a textbook for a graduate course summarizing thetheory and methods developed to deal with long-range-dependentdata, and describing some applications to real-life time series.“(SciTech Book Reviews, June 2007)
„... textbook for a graduate course summarizing the theory andmethods developed to deal with long-range-dependent data, anddescribing some applications to real-life time series.... Problemsand bibliographic notes are provided at the end of each chapter.“(SciTech Book News, June 2007)
„I believe that this text provides an important contribution tothe long-memory time series literature. I feel that it largelyachieves its aims and could be useful for those instructors wishingto teach a semester-long special topics course.... I stronglyrecommend this book to anyone interested in long-memory timeseries. Both researchers and beginners alike will find this textextremely useful.“ (Journal of the American StatisticialAssociation, Dec 2008)
„Very well-organized catalogue of long-memory time seriesanalysis.“ (Mathematical Reviews, 2008)
"Judging by its contents and scope [the aim of this book] hasbeen largely achieved.... The list of references is selective butquite comprehensive. Each chapter concludes with a 'Problems'section which should be helpful to instructors wishing to use thisbook as standalone basis for a course in its subject area..."(International Statistical Review, 2007)
Long-Memory Time Series: Theory and Methods provides an overviewof the theory and methods developed to deal with long-rangedependent data and describes the applications of thesemethodologies to real-life time series. Systematically organized, it begins with the foundational essentials, proceeds to theanalysis of methodological aspects (Estimation Methods, AsymptoticTheory, Heteroskedastic Models, Transformations, Bayesian Methods, and Prediction), and then extends these techniques to more complexdata structures.
To facilitate understanding, the book:
* Assumes a basic knowledge of calculus and linear algebra andexplains the more advanced statistical and mathematicalconcepts
* Features numerous examples that accelerate understanding andillustrate various consequences of the theoretical results
* Proves all theoretical results (theorems, lemmas, corollaries, etc.) or refers readers to resources with further demonstration
* Includes detailed analyses of computational aspects related tothe implementation of the methodologies described, includingalgorithm efficiency, arithmetic complexity, CPU times, andmore
* Includes proposed problems at the end of each chapter to helpreaders solidify their understanding and practice their skills
A valuable real-world reference for researchers andpractitioners in time series analysis, economerics, finance, andrelated fields, this book is also excellent for a beginninggraduate-level course in long-memory processes or as a supplementaltextbook for those studying advanced statistics, mathematics, economics, finance, engineering, or physics. A companion Web siteis available for readers to access the S-Plus and R data sets usedwithin the text.
