File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Population size estimation using local sample coverage for open populations

TitlePopulation size estimation using local sample coverage for open populations
Authors
KeywordsCapture-recapture
Kernel function
Martingale
Open population
Sample coverage
Issue Date2003
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jspi
Citation
Journal Of Statistical Planning And Inference, 2003, v. 113 n. 2, p. 699-714 How to Cite?
AbstractAn unsolved problem in the analysis of capture-recapture experiments is the estimation of the size of an open population when the capture probabilities are heterogeneous across the population. Here, we extend a kernel smoothing approach of Huggins and Yip (Biometrics 55 (1999) 387) to the martingale estimating functions based on sample coverage of Chao et al. (J. Statist. Plann. Inference 92 (2001) 213) and solve this problem when there are frequent capture occasions. Simulation results are shown to examine the performance of the proposed estimation procedure. A real data set is used for illustration. © 2002 Elsevier Science B.V. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/83015
ISSN
2022 Impact Factor: 0.9
2020 SCImago Journal Rankings: 0.622
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorHuggins, Ren_HK
dc.contributor.authorYang, HCen_HK
dc.contributor.authorChao, Aen_HK
dc.contributor.authorYip, PSFen_HK
dc.date.accessioned2010-09-06T08:35:58Z-
dc.date.available2010-09-06T08:35:58Z-
dc.date.issued2003en_HK
dc.identifier.citationJournal Of Statistical Planning And Inference, 2003, v. 113 n. 2, p. 699-714en_HK
dc.identifier.issn0378-3758en_HK
dc.identifier.urihttp://hdl.handle.net/10722/83015-
dc.description.abstractAn unsolved problem in the analysis of capture-recapture experiments is the estimation of the size of an open population when the capture probabilities are heterogeneous across the population. Here, we extend a kernel smoothing approach of Huggins and Yip (Biometrics 55 (1999) 387) to the martingale estimating functions based on sample coverage of Chao et al. (J. Statist. Plann. Inference 92 (2001) 213) and solve this problem when there are frequent capture occasions. Simulation results are shown to examine the performance of the proposed estimation procedure. A real data set is used for illustration. © 2002 Elsevier Science B.V. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jspien_HK
dc.relation.ispartofJournal of Statistical Planning and Inferenceen_HK
dc.rightsJournal of Statistical Planning and Inference. Copyright © Elsevier BV.en_HK
dc.subjectCapture-recaptureen_HK
dc.subjectKernel functionen_HK
dc.subjectMartingaleen_HK
dc.subjectOpen populationen_HK
dc.subjectSample coverageen_HK
dc.titlePopulation size estimation using local sample coverage for open populationsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0378-3758&volume=113&issue=2&spage=699&epage=714&date=2003&atitle=Population+size+estimation+using+local+sample+coverage+for+open+populationsen_HK
dc.identifier.emailYip, PSF: sfpyip@hku.hken_HK
dc.identifier.authorityYip, PSF=rp00596en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/S0378-3758(02)00093-9en_HK
dc.identifier.scopuseid_2-s2.0-0037408748en_HK
dc.identifier.hkuros82114en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0037408748&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume113en_HK
dc.identifier.issue2en_HK
dc.identifier.spage699en_HK
dc.identifier.epage714en_HK
dc.identifier.isiWOS:000181546700021-
dc.publisher.placeNetherlandsen_HK
dc.identifier.scopusauthoridHuggins, R=7102879186en_HK
dc.identifier.scopusauthoridYang, HC=8363972700en_HK
dc.identifier.scopusauthoridChao, A=7102703038en_HK
dc.identifier.scopusauthoridYip, PSF=7102503720en_HK
dc.identifier.issnl0378-3758-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats