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Springer Statistical Physics to Statistical Inference - Springer NATO 428

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Description

Explore the intersection of statistical physics and statistical inference with this comprehensive NATO Science Series volume. This book bridges the conceptual gap between physicists modelling complex systems with many degrees of freedom and statisticians performing rigorous data analysis, examining whether their inference methods are equivalent or distinct. Discover cutting-edge approaches to making optimal inferences across disciplines, with particular focus on neural computation, chaotic nonlinear systems applied to time series analysis, and how neural systems perform inference. Essential reading for researchers seeking to integrate physical theory with statistical methodology and advance understanding across computational and analytical fields.

Key Features

Springer NATO Science Series C volume 428 bridges physics-based and statistics-based inference approaches.

Examines equivalence and differences between physicists' and statisticians' methods for optimal inference.

Covers neural computation and how neural systems perform inference from data.

Applies chaotic nonlinear systems theory to time series analysis using statistical foundations.

Integrates physical theory with statistical methodology for complex systems modelling.

Addresses inference in systems with large numbers of degrees of freedom.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
31 March 1994
Listed Since
15 December 2006

Barcode

No barcode data available

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