A unified parametric regression model for recapture studies with random removals in continuous time

Conditional likelihood based on counting processes are combined with a Horvitz-Thompson estimator to yield a population size estimator that is more efficient than the existing ones. Random removals are allowed in the recapturing process. Simulation studies are shown to assess the performance of the proposed estimators. Examples on a bird banding and a small mammal recapturing study are given.