Statistics for Long-Memory Processes

This book serves as a comprehensive guide to statistical methods for analyzing long-range dependent data, providing both theory and practical applications.

In Statistics for Long-Memory Processes, the author delves into the various statistical methods and applications tailored for data exhibiting long-range dependence. By synthesizing material that has primarily been available in academic journals, the book offers a clear and concise overview of the probabilistic foundations and statistical techniques necessary for understanding this complex area. Emphasizing both fundamental principles and practical applications, it provides readers with an integrated view that bridges theory and real-world practice.

The text covers a diverse array of data sets from multiple disciplines, including hydrology, climatology, telecommunications engineering, and high-precision physical measurement. These examples are conveniently compiled in an index, allowing readers to explore statistical approaches in context. This practical focus ensures that the material is not only theoretical but also applicable to real-life scenarios, making it an invaluable resource for practitioners.

Additionally, Statistics for Long-Memory Processes includes S-PLUS programs for the key methods discussed, enabling practitioners to implement long-memory processes in their daily data analyses. For those new to the field, the initial chapters lay down the foundational knowledge required to engage with the subsequent content. The author has structured the chapters to promote selective reading, making this book an essential reference for statisticians and scientists working with long-range dependent data.