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CRC Press Parameter Redundancy and Identifiability - CRC Press Statistics

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Description

Parameter Redundancy and Identifiability from Chapman and Hall/CRC explores why certain model parameters cannot be estimated individually and addresses non-identifiability challenges in statistical and mathematical modelling. This interdisciplinary statistics book explains how parameters that appear together as products or in inseparable relationships create redundancy issues, preventing researchers from obtaining unique parameter estimates. The book is part of the Chapman and Hall/CRC Interdisciplinary Statistics series and covers the theoretical foundations and practical implications of parameter redundancy, offering essential guidance for statisticians, mathematicians, and researchers working with complex models where parameter estimation presents difficulties. Understanding these concepts is vital for developing reliable statistical models and avoiding the pitfalls of non-identifiable parameters.

Key Features

Chapman and Hall/CRC Interdisciplinary Statistics series book covering parameter redundancy and non-identifiability in statistical models.

Explains why certain parameters cannot be estimated individually and the consequences of parameter redundancy in mathematical modelling.

Explores the distinction between parameter redundant models and non-identifiable parameters for research applications.

Essential reference for statisticians and researchers working with complex models requiring robust parameter estimation techniques.

Comprehensive treatment of identifiability challenges in statistical and mathematical model development.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
26 May 2020
Listed Since
08 August 2018

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