Long-Memory Time Series (eBook)

Wilfredo Palma, PhD, is Chairman and Professor of Statistics in the Department of Statistics at Pontificia Universidad Católica de Chile. Dr. Palma has published several refereed articles and has received over a dozen academic honors and awards. His research interests include time series analysis, prediction theory, state space systems, linear models, and econometrics.

Preface.

Acronyms.

1. Stationary Processes.

2. State Space Systems.

3. Long-Memory Processes.

4. Estimation Methods.

5. Asymptotic Theory.

6. Heteroskedastic Models.

7. Transformations.

8. Bayesian Methods.

9. Prediction.

10. Regression.

11. Missing Data.

12. Seasonality.

References.

Topic Index.

Author Index.

"...Palma presents a textbook for a graduate course summarizing the
theory and methods developed to deal with long-range-dependent
data, and describing some applications to real-life time series."
(SciTech Book Reviews, June 2007)

"...textbook for a graduate course summarizing the theory and
methods developed to deal with long-range-dependent data, and
describing some applications to real-life time series.... Problems
and bibliographic notes are provided at the end of each chapter."
(SciTech Book News, June 2007)

"I believe that this text provides an important contribution to
the long-memory time series literature. I feel that it largely
achieves its aims and could be useful for those instructors wishing
to teach a semester-long special topics course.... I strongly
recommend this book to anyone interested in long-memory time
series. Both researchers and beginners alike will find this text
extremely useful." (Journal of the American Statisticial
Association, Dec 2008)

"Very well-organized catalogue of long-memory time series
analysis." (Mathematical Reviews, 2008)

"Judging by its contents and scope [the aim of this book] has
been largely achieved.... The list of references is selective but
quite comprehensive. Each chapter concludes with a 'Problems'
section which should be helpful to instructors wishing to use this
book as standalone basis for a course in its subject area..."
(International Statistical Review, 2007)