Assessing heterogeneity in transition propensity in multi-state capture-recapture data
Multi-state capture-recapture models are a useful tool to help understand the dynamics of movement within discrete capture-recapture data. The standard multi-state capture-recapture model however relies on assumptions of homogeneity within the population with respect to survival, capture and transit...
| Published in: | Journal of the Royal Statistical Society: Series C (Applied Statistics) |
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| Main Authors: | , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Wiley
2020
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| Subjects: | |
| Online Access: | https://kar.kent.ac.uk/78386/ https://kar.kent.ac.uk/78386/11/Jeyam_et_al-2019-Journal_of_the_Royal_Statistical_Society__Series_C_%28Applied_Statistics%29.pdf https://kar.kent.ac.uk/78386/1/main_revision2.pdf https://doi.org/10.1111/rssc.12392 |
| Summary: | Multi-state capture-recapture models are a useful tool to help understand the dynamics of movement within discrete capture-recapture data. The standard multi-state capture-recapture model however relies on assumptions of homogeneity within the population with respect to survival, capture and transition probabilities. There are many ways in which this model can be generalized so that some guidance as to what is really needed is highly desirable. Within this paper we derive a new test capable of detecting heterogeneity in transition propensity and show its good power using simulation and application to a Canada goose data set. We also demonstrate that existing tests which have traditionally been used to diagnose memory are in fact sensitive to other forms of transition heterogeneity and we propose modified tests which are able to distinguish between memory and other forms of transition heterogeneity. |
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