期刊
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
卷 81, 期 12, 页码 1879-1895出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00949655.2010.507764
关键词
generalized hypergeometric distribution; parametric bootstrap; point estimation; interval estimation; coverage probability
资金
- National Science Foundation [DMS-0718465, DUE-0531915]
This paper deals with estimation of a green tree frog population in an urban setting using repeated capture-mark-recapture (CMR) method over several weeks with an individual tagging system which gives rise to a complicated generalization of the hypergeometric distribution. Based on the maximum likelihood estimation, a parametric bootstrap approach is adopted to obtain interval estimates of the weekly population size which is the main objective of our work. The method is computation-based; and programming intensive to implement the algorithm for re-sampling. This method can be applied to estimate the population size of any species based on repeated CMR method at multiple time points. Further, it has been pointed out that the well-known Jolly-Seber method, which is based on some strong assumptions, produces either unrealistic estimates, or may have situations where its assumptions are not valid for our observed data set.
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