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Parameter Redundancy in Discrete State-Space and Integrated Models

Cole, Diana J., McCrea, Rachel S. (2016) Parameter Redundancy in Discrete State-Space and Integrated Models. Biometrical Journal, 58 (5). pp. 1071-1090. ISSN 0323-3847. E-ISSN 1521-4036. (doi:10.1002/bimj.201400239) (KAR id:41228)


Discrete state-space models are used in ecology to describe the dynamics of wild animal populations, with parameters, such as the probability of survival, being of ecological interest. For a particular parametrisation of a model it is not always clear which parameters can be estimated. This inability to estimate all parameters is known as parameter redundancy or a model is described as non-identifiable. In this paper we develop methods that can be used to detect parameter redundancy in discrete state-space models. An exhaustive summary is a combination of parameters that fully specify a model. To use general methods for detecting parameter redundancy a suitable exhaustive summary is required. This paper proposes two methods for the derivation of an exhaustive summary for discrete state-space models using discrete analogues of methods for continuous state-space models. We also demonstrate that combining multiple data sets, through the use of an integrated population model, may result in a model in which all parameters are estimable, even though models fitted to the separate data sets may be parameter redundant.

Item Type: Article
DOI/Identification number: 10.1002/bimj.201400239
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: 30 May 2014 09:09 UTC
Last Modified: 16 Feb 2021 12:53 UTC
Resource URI: (The current URI for this page, for reference purposes)

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