Parameter Redundancy in Discrete State-Space and Integrated Models

Cole, Diana J. and 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:https://doi.org/10.1002/bimj.201400239) (Full text available)

Abstract

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
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions: Faculties > Sciences > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Diana Cole
Date Deposited: 30 May 2014 09:09 UTC
Last Modified: 08 Jun 2017 08:44 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/41228 (The current URI for this page, for reference purposes)
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