Assessing heterogeneity in transition propensity in multistate capture-recapture data

• Published in: Journal of the Royal Statistical Society Series C: Applied Statistics
• Main Authors: Jeyam, Anita, Mccrea, Rachel S., Pradel, Roger
• Other Authors: University of Kent Canterbury, Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD France-Sud )-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2020
• Subjects: Markovian transitions; Goodness of fit; Diagnostics; [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]; [SDE.BE]Environmental Sciences/Biodiversity and Ecology; Canada; Canada Goose
• Online Access: https://hal.science/hal-02387535; https://hal.science/hal-02387535/document; https://hal.science/hal-02387535/file/Jeyam%202019-Journal_of_the_Royal_Statistical_Society__Series_C_%28Applied_Statistics%29%20%281%29.pdf; https://doi.org/10.1111/rssc.12392

International audience Multistate capture-recapture models are a useful tool to help to understand the dynamics of movement within discrete capture-recapture data.The standard multistate 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 some guidance on what is really needed is highly desirable. Within the paper we derive a new test that can detect heterogeneity in transition propensity and show its good power by 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 can distinguish between memory and other forms of transition heterogeneity.