Confidence intervals for population size based on a capture-recapture design

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dc.contributor.author Hua, Jianjun
dc.date.accessioned 2011-11-21T20:59:01Z
dc.date.available 2011-11-21T20:59:01Z
dc.date.issued 2011-11-21
dc.identifier.uri http://hdl.handle.net/2097/13103
dc.description.abstract Capture-Recaputre (CR) experiments stemmed from the study of wildlife and are widely used in areas such as ecology, epidemiology, evaluation of census undercounts, and software testing, to estimate population size, survival rate, and other population parameters. The basic idea of the design is to use “overlapping” information contained in multiple samples from the population. In this report, we focus on the simplest form of Capture-Recapture experiments, namely, a two-sample Capture-Recapture design, which is conventionally called the “Petersen Method.” We study and compare the performance of three methods of constructing confidence intervals for the population size based on a Capture-Recapture design, asymptotic normality estimation, Chapman estimation, and “inverting a chi-square test” estimation, in terms of coverage rate and mean interval width. Simulation studies are carried out and analyzed using R and SAS. It turns out that the “inverting a chi-square test” estimation is better than the other two methods. A possible solution to the “zero recapture” problem is put forward. We find that if population size is at least a few thousand, two-sample CR estimation provides reasonable estimates of the population size. en_US
dc.language.iso en_US en_US
dc.publisher Kansas State University en
dc.subject Capture-recapture en_US
dc.subject Confidence interval en_US
dc.subject Population size en_US
dc.subject Asymptotic normality estimation en_US
dc.subject Inverting a test en_US
dc.subject Coverage rate en_US
dc.title Confidence intervals for population size based on a capture-recapture design en_US
dc.type Report en_US
dc.description.degree Master of Science en_US
dc.description.level Masters en_US
dc.description.department Department of Statistics en_US
dc.description.advisor Paul I. Nelson en_US
dc.subject.umi Statistics (0463) en_US
dc.date.published 2011 en_US
dc.date.graduationmonth December en_US


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