Translator Disclaimer
February 2016 Likelihood-based inference for population size in a capture–recapture experiment with varying probabilities from occasion to occasion
Luis Ernesto Bueno Salasar, José Galvão Leite, Francisco Louzada
Braz. J. Probab. Stat. 30(1): 47-69 (February 2016). DOI: 10.1214/14-BJPS255

Abstract

The estimation of the size of a population is, in general, performed using capture–recapture experiments. In this paper, we consider a closed population capture–recapture model in which individuals are captured independently and with the same probability in each sampling occasion, but the probabilities may vary from occasion to occasion. The unknown number of individuals is the parameter of interest, while the capture probabilities are the nuisance ones. Four likelihood functions free of nuisance parameters, namely the profile, conditional, uniform and Jeffrey’s integrated likelihood functions are derived and procedures for point and interval estimation are discussed. The estimation of population size is illustrated on a real dataset. The frequentist properties of the estimators are evaluated by means of a simulation study. The Jeffrey’s integrated likelihood achieved the best performance over all considered estimators for both point and interval estimation, particularly in situations with little information with small number of elements, small capture probabilities and small number of capture occasions.

Citation

Download Citation

Luis Ernesto Bueno Salasar. José Galvão Leite. Francisco Louzada. "Likelihood-based inference for population size in a capture–recapture experiment with varying probabilities from occasion to occasion." Braz. J. Probab. Stat. 30 (1) 47 - 69, February 2016. https://doi.org/10.1214/14-BJPS255

Information

Received: 1 June 2013; Accepted: 1 July 2014; Published: February 2016
First available in Project Euclid: 19 January 2016

zbMATH: 1381.62029
MathSciNet: MR3453514
Digital Object Identifier: 10.1214/14-BJPS255

Rights: Copyright © 2016 Brazilian Statistical Association

JOURNAL ARTICLE
23 PAGES


SHARE
Vol.30 • No. 1 • February 2016
Back to Top