Statistics for Long-Memory Processes

1st Edition

Jan Beran

Chapman and Hall/CRC
Published October 1, 1994
Reference - 315 Pages
ISBN 9780412049019 - CAT# C4901
Series: Chapman & Hall/CRC Monographs on Statistics & Applied Probability


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  • Provides simple solutions to location estimation, optimal forecasting, model fitting, regression, analysis of variance, goodness-of-fit tests, and detection of long memory
  • Helps in the prevention of erroneous conclusions that may stem from ignoring the existence and/or effect of slowly slowly decaying correlations
  • Provides data sets and practical solutions on how to handle them
  • Promotes a better understanding of phenomena such as the occurrence of local trends, local cycles, and power spectra in many time series
  • Summary

    Statistical Methods for Long Term Memory Processes covers the diverse statistical methods and applications for data with long-range dependence. Presenting material that previously appeared only in journals, the author provides a concise and effective overview of probabilistic foundations, statistical methods, and applications. The material emphasizes basic principles and practical applications and provides an integrated perspective of both theory and practice. This book explores data sets from a wide range of disciplines, such as hydrology, climatology, telecommunications engineering, and high-precision physical measurement. The data sets are conveniently compiled in the index, and this allows readers to view statistical approaches in a practical context.

    Statistical Methods for Long Term Memory Processes also supplies S-PLUS programs for the major methods discussed. This feature allows the practitioner to apply long memory processes in daily data analysis. For newcomers to the area, the first three chapters provide the basic knowledge necessary for understanding the remainder of the material. To promote selective reading, the author presents the chapters independently. Combining essential methodologies with real-life applications, this outstanding volume is and indispensable reference for statisticians and scientists who analyze data with long-range dependence.