{"id":{"repo_id":"unlv","oai_identifier":"oai:oasis.library.unlv.edu:rtds-1890"},"canonical_url":"https://search.dev.ndltd.org/etd/unlv/oai:oasis.library.unlv.edu:rtds-1890","repository":{"repo_id":"unlv","name":"University of Nevada - Las Vegas","base_url":"https://oasis.library.unlv.edu/do/oai/"},"display":{"title":"Population size estimation from mark-resighting surveys","abstract":"We consider the problem of estimating the size of a closed population based on the results of a certain type of marking-resighting sampling design. The design is similar to the commonly used multiple capture-recapture design, yet in some cases economically more feasible and easy to use. Sampling is done by first tagging a number of randomly selected animals with visible markers and later randomly sighting them (for instance, for large animals by visually sampling from a helicopter) and counting the number of tagged animals; In this paper, by using the above mentioned sampling scheme we present the maximum likelihood estimation (MLE) and Bayesian estimation of N by using different methods and construct their confidence intervals. We also use real data sets and simulated data sets to test these statistical indexes, and we find that it is reasonable for us to construct the confidence intervals of N by using these methods and that the approximate confidence interval of N is reliable.","abstract_html":"We consider the problem of estimating the size of a closed population based on the results of a certain type of marking-resighting sampling design. The design is similar to the commonly used multiple capture-recapture design, yet in some cases economically more feasible and easy to use. Sampling is done by first tagging a number of randomly selected animals with visible markers and later randomly sighting them (for instance, for large animals by visually sampling from a helicopter) and counting the number of tagged animals; In this paper, by using the above mentioned sampling scheme we present the maximum likelihood estimation (MLE) and Bayesian estimation of N by using different methods and construct their confidence intervals. We also use real data sets and simulated data sets to test these statistical indexes, and we find that it is reasonable for us to construct the confidence intervals of N by using these methods and that the approximate confidence interval of N is reliable.","abstract_has_math":false,"creators":["He, Huawen"],"institution":"University of Nevada, Las Vegas","degree_name":"Master of Science (MS)","degree_level":"Thesis","degree_discipline":"Mathematical Sciences","degree_department":null,"school":null,"contributors":["Malwane Ananda"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1998,"date_issued":"1998-01-01T08:00:00Z","date_published":"1998-01-01T08:00:00Z","updated_at":"2026-07-24T05:24:45Z","subjects":[],"languages":[],"rights":["IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://oasis.library.unlv.edu/rtds/891"],"render_values":[{"text":"https://oasis.library.unlv.edu/rtds/891","href":"https://oasis.library.unlv.edu/rtds/891","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.25669/6l92-eyaw","outbound_label":"DOI","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Malwane Ananda"]},{"key":"dc:creator","label":"Author","values":["He, Huawen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:publisher","label":"Institution","values":["University of Nevada, Las Vegas"]},{"key":"dc:type","label":"Dc Type","values":["Text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mathematical Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS)"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["IN COPYRIGHT. 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Sampling is done by first tagging a number of randomly selected animals with visible markers and later randomly sighting them (for instance, for large animals by visually sampling from a helicopter) and counting the number of tagged animals; In this paper, by using the above mentioned sampling scheme we present the maximum likelihood estimation (MLE) and Bayesian estimation of N by using different methods and construct their confidence intervals. We also use real data sets and simulated data sets to test these statistical indexes, and we find that it is reasonable for us to construct the confidence intervals of N by using these methods and that the approximate confidence interval of N is reliable."]},{"key":"dc:format","label":"Dc Format","values":["pdf"]},{"key":"dc:title","label":"Title","values":["Population size estimation from mark-resighting surveys"]}]}],"canonical_facts":{"dc:contributor":["Malwane Ananda"],"dc:creator":["He, Huawen"],"dc:description.abstract":["We consider the problem of estimating the size of a closed population based on the results of a certain type of marking-resighting sampling design. The design is similar to the commonly used multiple capture-recapture design, yet in some cases economically more feasible and easy to use. Sampling is done by first tagging a number of randomly selected animals with visible markers and later randomly sighting them (for instance, for large animals by visually sampling from a helicopter) and counting the number of tagged animals; In this paper, by using the above mentioned sampling scheme we present the maximum likelihood estimation (MLE) and Bayesian estimation of N by using different methods and construct their confidence intervals. We also use real data sets and simulated data sets to test these statistical indexes, and we find that it is reasonable for us to construct the confidence intervals of N by using these methods and that the approximate confidence interval of N is reliable."],"dc:format":["pdf"],"dc:identifier":["10.25669/6l92-eyaw","https://oasis.library.unlv.edu/rtds/891","https://oasis.library.unlv.edu/context/rtds/article/1890/viewcontent/uc.pdf"],"dc:publisher":["University of Nevada, Las Vegas"],"dc:rights":["IN COPYRIGHT. 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