Parameter redundancy in discrete state-space and integrated models : Parameter redundancy in discrete state-space and integrated models

Cole, Diana J. and McCrea, Rachel (2016) Parameter redundancy in discrete state-space and integrated models : Parameter redundancy in discrete state-space and integrated models. Biom. J., 58 (5). pp. 1071-1090. ISSN 0323-3847

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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 parametrization 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 nonidentifiable. 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:
Journal Article
Journal or Publication Title:
Biom. J.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
?? capture-recaptureidentifiabilityjoint likelihoodmark-recovery modelspopulation dynamicsstatistics and probabilitystatistics, probability and uncertaintygeneral medicinemedicine(all) ??
ID Code:
176516
Deposited By:
Deposited On:
10 Oct 2022 11:20
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Jul 2024 11:54