![]() ![]() Individuals are uniquely identified, using, for example, a ring or tag applied at initial capture or via natural markings. Observations at each capture occasion may take the form of physical captures and/or visual sightings of animals. These surveys involve repeatedly sampling the population over a series of capture occasions. We find that for the situations considered, the Laplace approximation performs as well as, or better, than alternative approaches, yet is substantially more efficient.Supplementary materials accompanying this paper appear on-lineĬapture–recapture surveys are often used when studying wildlife populations to understand the associated population dynamics necessary for management and conservation. We propose a new and efficient approach that approximates the analytically intractable integral in the likelihood via a Laplace approximation. However, as the number of individuals observed and/or capture occasions increases, these methods can become computationally expensive. Previous approaches to dealing with these issues include numerical integration and Bayesian data augmentation techniques. The integration is specified over (i) the unknown individual covariate values (if an individual is not observed, its associated covariate value is also unknown) and (ii) the unobserved random effect terms. In general, the associated likelihood is not available in closed form but only expressible as an analytically intractable integral. We consider (i) continuous time-varying individual covariates and (ii) individual random effects. We focus on the most challenging of these relating to individual heterogeneity. Populations in such studies are often subject to different forms of heterogeneity that may influence their associated demographic rates. ![]() Capture–recapture studies are common for collecting data on wildlife populations. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |