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

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Parameter redundancy in discrete state-space and integrated models: Parameter redundancy in discrete state-space and integrated models. / Cole, Diana J.; McCrea, Rachel.
In: Biom. J., Vol. 58, No. 5, 30.09.2016, p. 1071-1090.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Cole, DJ & McCrea, R 2016, 'Parameter redundancy in discrete state-space and integrated models: Parameter redundancy in discrete state-space and integrated models', Biom. J., vol. 58, no. 5, pp. 1071-1090. https://doi.org/10.1002/bimj.201400239

APA

Cole, D. J., & McCrea, R. (2016). Parameter redundancy in discrete state-space and integrated models: Parameter redundancy in discrete state-space and integrated models. Biom. J., 58(5), 1071-1090. https://doi.org/10.1002/bimj.201400239

Vancouver

Cole DJ, McCrea R. Parameter redundancy in discrete state-space and integrated models: Parameter redundancy in discrete state-space and integrated models. Biom. J. 2016 Sept 30;58(5): 1071-1090. Epub 2016 Jun 30. doi: 10.1002/bimj.201400239

Author

Cole, Diana J. ; McCrea, Rachel. / Parameter redundancy in discrete state-space and integrated models : Parameter redundancy in discrete state-space and integrated models. In: Biom. J. 2016 ; Vol. 58, No. 5. pp. 1071-1090.

Bibtex

@article{48c14143470e4be08a2772943e68173e,
title = "Parameter redundancy in discrete state-space and integrated models: Parameter redundancy in discrete state-space and integrated models",
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.",
keywords = "Capture-recapture, Identifiability, Joint likelihood, Mark-recovery models, Population dynamics",
author = "Cole, {Diana J.} and Rachel McCrea",
year = "2016",
month = sep,
day = "30",
doi = "10.1002/bimj.201400239",
language = "English",
volume = "58",
pages = " 1071--1090",
journal = "Biom. J.",
issn = "0323-3847",
publisher = "Wiley-VCH Verlag",
number = "5",

}

RIS

TY - JOUR

T1 - Parameter redundancy in discrete state-space and integrated models

T2 - Parameter redundancy in discrete state-space and integrated models

AU - Cole, Diana J.

AU - McCrea, Rachel

PY - 2016/9/30

Y1 - 2016/9/30

N2 - 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.

AB - 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.

KW - Capture-recapture

KW - Identifiability

KW - Joint likelihood

KW - Mark-recovery models

KW - Population dynamics

U2 - 10.1002/bimj.201400239

DO - 10.1002/bimj.201400239

M3 - Journal article

VL - 58

SP - 1071

EP - 1090

JO - Biom. J.

JF - Biom. J.

SN - 0323-3847

IS - 5

ER -