A nonparametric method of estimation of the population size in capture–recapture experiments. Issue 4 (29th January 2020)

• Record Type: Journal Article
• Authors: Jiménez‐Gamero, María Dolores; Puig, Pedro
• Is Part Of: Biometrical journal. Volume 62:Issue 4(2020:Jul.)
• Page Start: 970
• Page End: 988
• Publication Date: 2020-01-29
• Subjects: asymptotic normality -- Chao's estimator -- empirical probability generating function -- LC‐class -- Turing's estimator -- zero‐truncated count distributions; Biometry -- Periodicals; Medical statistics -- Periodicals; 570.15195
• DOI: 10.1002/bimj.201900185
• Languages: English
• ISSNs: 0323-3847

Abstract

Abstract: A recent method for estimating a lower bound of the population size in capture–recapture samples is studied. Specifically, some asymptotic properties, such as strong consistency and asymptotic normality, are provided. The introduced estimator is based on the empirical probability generating function (pgf) of the observed data, and it is consistent for count distributions having a log‐convex pgf ( L C ‐class). This is a large family that includes mixed and compound Poisson distributions, and their independent sums and finite mixtures as well. The finite‐sample performance of the lower bound estimator is assessed via simulation showing a better behavior than some close competitors. Several examples of application are also analyzed and discussed.