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Probit Models For Capture-Recapture Data Subject To Imperfect Detection, Individual Heterogeneity And Misidentification1, Brett T. Mcclintock, Larissa L. Bailey, Brian P. Dreher, William A. Link
Probit Models For Capture-Recapture Data Subject To Imperfect Detection, Individual Heterogeneity And Misidentification1, Brett T. Mcclintock, Larissa L. Bailey, Brian P. Dreher, William A. Link
United States Geological Survey: Staff Publications
As noninvasive sampling techniques for animal populations have become more popular, there has been increasing interest in the development of capture-recapture models that can accommodate both imperfect detection and misidentification of individuals (e.g., due to genotyping error). However, current methods do not allow for individual variation in parameters, such as detection or survival probability. Here we develop misidentification models for capture-recapture data that can simultaneously account for temporal variation, behavioral effects and individual heterogeneity in parameters. To facilitate Bayesian inference using our approach, we extended standard probit regression techniques to latent multinomial models where the dimension and zeros of the …
Probit Models For Capture-Recapture Data Subject To Imperfect Detection, Individual Heterogeneity And Misidentification, Brett T. Mcclinktock, Larissa L. Bailey, Brian P. Dreher, William A. Link
Probit Models For Capture-Recapture Data Subject To Imperfect Detection, Individual Heterogeneity And Misidentification, Brett T. Mcclinktock, Larissa L. Bailey, Brian P. Dreher, William A. Link
United States Geological Survey: Staff Publications
As noninvasive sampling techniques for animal populations have become more popular, there has been increasing interest in the development of capture-recapture models that can accommodate both imperfect detection and misidentification of individuals (e.g., due to genotyping error). However, current methods do not allow for individual variation in parameters, such as detection or survival probability. Here we develop misidentification models for capture-recapture data that can simultaneously account for temporal variation, behavioral effects and individual heterogeneity in parameters. To facilitate Bayesian inference using our approach, we extend standard probit regression techniques to latent multinomial models where the dimension and zeros of the …