{"title":"Small Sample Inference for Two‐Way Capture‐Recapture Experiments","authors":"Louis‐Paul Rivest, Mamadou Yauck","doi":"10.1111/insr.12574","DOIUrl":null,"url":null,"abstract":"SummaryThe properties of the generalised Waring distribution defined on the non‐negative integers are reviewed. Formulas for its moments and its mode are given. A construction as a mixture of negative binomial distributions is also presented. Then we turn to the Petersen model for estimating the population size in a two‐way capture‐recapture experiment. We construct a Bayesian model for by combining a Waring prior with the hypergeometric distribution for the number of units caught twice in the experiment. Credible intervals for are obtained using quantiles of the posterior, a generalised Waring distribution. The standard confidence interval for the population size constructed using the asymptotic variance of Petersen estimator and 0.5 logit transformed interval are shown to be special cases of the generalised Waring credible interval. The true coverage of this interval is shown to be bigger than or equal to its nominal converage in small populations, regardless of the capture probabilities. In addition, its length is substantially smaller than that of the 0.5 logit transformed interval. Thus, the proposed generalised Waring credible interval appears to be the best way to quantify the uncertainty of the Petersen estimator for populations size.","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Statistical Review","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1111/insr.12574","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
SummaryThe properties of the generalised Waring distribution defined on the non‐negative integers are reviewed. Formulas for its moments and its mode are given. A construction as a mixture of negative binomial distributions is also presented. Then we turn to the Petersen model for estimating the population size in a two‐way capture‐recapture experiment. We construct a Bayesian model for by combining a Waring prior with the hypergeometric distribution for the number of units caught twice in the experiment. Credible intervals for are obtained using quantiles of the posterior, a generalised Waring distribution. The standard confidence interval for the population size constructed using the asymptotic variance of Petersen estimator and 0.5 logit transformed interval are shown to be special cases of the generalised Waring credible interval. The true coverage of this interval is shown to be bigger than or equal to its nominal converage in small populations, regardless of the capture probabilities. In addition, its length is substantially smaller than that of the 0.5 logit transformed interval. Thus, the proposed generalised Waring credible interval appears to be the best way to quantify the uncertainty of the Petersen estimator for populations size.
期刊介绍:
International Statistical Review is the flagship journal of the International Statistical Institute (ISI) and of its family of Associations. It publishes papers of broad and general interest in statistics and probability. The term Review is to be interpreted broadly. The types of papers that are suitable for publication include (but are not limited to) the following: reviews/surveys of significant developments in theory, methodology, statistical computing and graphics, statistical education, and application areas; tutorials on important topics; expository papers on emerging areas of research or application; papers describing new developments and/or challenges in relevant areas; papers addressing foundational issues; papers on the history of statistics and probability; white papers on topics of importance to the profession or society; and historical assessment of seminal papers in the field and their impact.