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A Test for the Underlying State-Structure of Hidden Markov Models: Partially Observed Capture-Recapture Data

Jeyam, Anita, McCrea, Rachel S., Pradel, Roger (2021) A Test for the Underlying State-Structure of Hidden Markov Models: Partially Observed Capture-Recapture Data. Frontiers in Ecology and Evolution, 9 . ISSN 2296-701X. (doi:10.3389/fevo.2021.598325) (KAR id:86960)

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Official URL
https://doi.org/10.3389/fevo.2021.598325

Abstract

Hidden Markov models (HMMs) are being widely used in the field of ecological modeling, however determining the number of underlying states in an HMM remains a challenge. Here we examine a special case of capture-recapture models for open populations, where some animals are observed but it is not possible to ascertain their state (partial observations), whilst the other animals' states are assigned without error (complete observations). We propose a mixture test of the underlying state structure generating the partial observations, which assesses whether they are compatible with the set of states observed in the complete observations. We demonstrate the good performance of the test using simulation and through application to a data set of Canada Geese.

Item Type: Article
DOI/Identification number: 10.3389/fevo.2021.598325
Uncontrolled keywords: multievent model, capture-recapture, partial observations, mixture of multinomials, Hidden markov model
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Rachel McCrea
Date Deposited: 05 Mar 2021 12:00 UTC
Last Modified: 05 Mar 2021 12:01 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/86960 (The current URI for this page, for reference purposes)
McCrea, Rachel S.: https://orcid.org/0000-0002-3813-5328
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