Estimation of Population Size When Capture Probability Depends on Individual States

Worthington, Hannah and McCrea, Rachel and King, Ruth and Griffiths, Richard A. (2019) Estimation of Population Size When Capture Probability Depends on Individual States. Journal of Agricultural, Biological and Environmental Statistics, 24 (1). pp. 154-172. ISSN 1085-7117

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Abstract

We develop a multi-state model to estimate the size of a closed population from capture–recapture studies. We consider the case where capture–recapture data are not of a simple binary form, but where the state of an individual is also recorded upon every capture as a discrete variable. The proposed multi-state model can be regarded as a generalisation of the commonly applied set of closed population models to a multi-state form. The model allows for heterogeneity within the capture probabilities associated with each state while also permitting individuals to move between the different discrete states. A closed-form expression for the likelihood is presented in terms of a set of sufficient statistics. The link between existing models for capture heterogeneity is established, and simulation is used to show that the estimate of population size can be biased when movement between states is not accounted for. The proposed unconditional approach is also compared to a conditional approach to assess estimation bias. The model derived in this paper is motivated by a real ecological data set on great crested newts, Triturus cristatus. Supplementary materials accompanying this paper appear online.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Agricultural, Biological and Environmental Statistics
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2604
Subjects:
?? ABUNDANCECLOSED POPULATIONINDIVIDUAL HETEROGENEITYTRANSITION PROBABILITIESSTATISTICS AND PROBABILITYENVIRONMENTAL SCIENCE(ALL)AGRICULTURAL AND BIOLOGICAL SCIENCES (MISCELLANEOUS)AGRICULTURAL AND BIOLOGICAL SCIENCES(ALL)STATISTICS, PROBABILITY AND UNCERTAI ??
ID Code:
176510
Deposited By:
Deposited On:
12 Oct 2022 11:45
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Sep 2023 02:33