Assessing heterogeneity in transition propensity in multistate capture-recapture data

Anita Jeyam (1) , Rachel S. Mccrea (1) , Roger Pradel (2)

1 University of Kent [Canterbury]
2 CEFE - Centre d’Ecologie Fonctionnelle et Evolutive

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.

Mots clés: Markovian transitions; Goodness of fit; Diagnostics

Domaines: Statistiques [math.ST]; Biodiversité et Ecologie

Anita Jeyam, Rachel S. Mccrea, Roger Pradel. Assessing heterogeneity in transition propensity in multistate capture-recapture data. Journal of the Royal Statistical Society: Series C Applied Statistics, 2020, 69 (2), pp.413-427. ⟨10.1111/rssc.12392⟩. ⟨hal-02387535⟩