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Parameter Redundancy and Identifiability

Cole, Diana J. (2020) Parameter Redundancy and Identifiability. Chapman and Hall/CRC ISBN 978-1-4987-2087-8. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:81374)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
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Abstract

Statistical and mathematical models are defined by parameters that describe different characteristics of those models. Ideally it would be possible to find parameter estimates for every parameter in that model, but, in some cases, this is not possible. For example, two parameters that only ever appear in the model as a product could not be estimated individually; only the product can be estimated. Such a model is said to be parameter redundant, or the parameters are described as non-identifiable. This book explains why parameter redundancy and non-identifiability is a problem and the different methods that can be used for detection, including in a Bayesian context.

Item Type: Book
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Diana Cole
Date Deposited: 26 May 2020 12:14 UTC
Last Modified: 16 Feb 2021 14:13 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/81374 (The current URI for this page, for reference purposes)
Cole, Diana J.: https://orcid.org/0000-0002-8109-4832
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