£108.78

Springer Correlation Theory of Stationary Random Functions Vol I

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Description

Explore the advanced mathematical foundations of modern probability theory with this essential text from the Springer Series in Statistics. This volume focuses on the theory of random functions, providing a deep look into the mathematical structures that drive contemporary statistical analysis. This book is particularly useful for those studying stationary random functions. These functions appear frequently in real-world applications where observations depend on time, whether that time is real-valued or integer-valued. By examining series of observations that fluctuate around a constant mean level without systematic changes, readers gain a clear understanding of how to handle disordered fluctuations in data. Designed for researchers and students in mathematics and statistics, this volume provides the basic results necessary to master the behavior of time series and stationary processes. It serves as a fundamental resource for anyone looking to understand the mathematical principles behind complex random processes.

Key Features

Covers the advanced mathematical theory of random functions within modern probability theory.

Focuses on stationary random functions, which are vital for analyzing data that fluctuates around a constant mean.

Provides a mathematical framework for understanding time series observations that depend on real-valued or integer-valued arguments.

Part of the respected Springer Series in Statistics, ensuring high-quality academic content.

Explains how to manage observations that undergo disordered fluctuations rather than systematic changes.

Product Specifications

Format
Paperback
Domain
Amazon UK
Release Date
06 October 2011
Listed Since
13 July 2012

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No barcode data available

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