1st Edition

Statistics for Long-Memory Processes

By Jan Beran Copyright 1994
    315 Pages
    by Chapman & Hall

    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.

    Preface
    Introduction
    Stationary Processes with Long Memory
    Limit Theorems
    Estimations of Long Memory-Heuristic Approaches
    Estimations of Long Memory-MLE Time Domain
    Estimations of Long Memory-MLE Frequency Domain
    Robust Estimation of Long Memory
    Estimation of Location and Scale, Forecasting
    Regression
    Goodness of Fit Tests and Related Topics
    References
    Author Index
    Subject Index

    Biography

    Jan Beran

    "This book covers the diverse statistical methods and applications for data with long-range dependence. The author provides a concise and accessible overview of probabilistic foundations, statistical methods, and applications."
    - L'Enseignement Mathematique

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