AI Article Synopsis

  • A general theory is proposed for estimating the size of a closed population using multiple-recapture data, and this theory can also be adapted for open population models.
  • The estimation process utilizes a log-linear model that accounts for variations in capture probabilities due to time and animal behavior.
  • Models are created for both complete capture histories and the first log-linear models for removal data, including a maximum likelihood estimator for model parameters and their covariance matrix.

Article Abstract

A general theory for estimating the size of a closed population from multiple-recapture data is presented. This theory is easily extended to open population models for multiple-recapture data. Estimation is based on a log-linear model developed for modeling dependent capture-recapture data when capture probabilities vary temporally with behavioral response and are heterogeneous among animals. Models for complete capture history data are developed along with the first log-linear models for removal data. The maximum likelihood estimator of the model parameters along with the estimated covariance matrix are presented.

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