An extravariation model for improving confidence intervals of population size estimates from removal data
We propose a new model for estimating the size of a population from successive catches taken during a removal experiment. The data from these experiments often have excessive variation, known as overdispersion, as compared with that predicted by the multinomial model. The new model allows catchabili...
Published in: | Canadian Journal of Fisheries and Aquatic Sciences |
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National Research Council Canada
1996
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ftqueensland:oai:eprints.qut.edu.au:90492 2024-01-21T10:09:57+01:00 An extravariation model for improving confidence intervals of population size estimates from removal data Wang, Y-G. Loneragan, N. R. 1996 https://eprints.qut.edu.au/90492/ unknown National Research Council Canada doi:10.1139/cjfas-53-11-2533 Wang, Y-G. & Loneragan, N. R. (1996) An extravariation model for improving confidence intervals of population size estimates from removal data. Canadian Journal of Fisheries and Aquatic Sciences, 53(11), pp. 2533-2539. https://eprints.qut.edu.au/90492/ Science & Engineering Faculty Consult author(s) regarding copyright matters This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au Canadian Journal of Fisheries and Aquatic Sciences likelihood-estimation recapture fish Contribution to Journal 1996 ftqueensland https://doi.org/10.1139/cjfas-53-11-2533 2023-12-25T23:20:20Z We propose a new model for estimating the size of a population from successive catches taken during a removal experiment. The data from these experiments often have excessive variation, known as overdispersion, as compared with that predicted by the multinomial model. The new model allows catchability to vary randomly among samplings, which accounts for overdispersion. When the catchability is assumed to have a beta distribution, the likelihood function, which is refered to as beta-multinomial, is derived, and hence the maximum likelihood estimates can be evaluated. Simulations show that in the presence of extravariation in the data, the confidence intervals have been substantially underestimated in previous models (Leslie-DeLury, Moran) and that the new model provides more reliable confidence intervals. The performance of these methods was also demonstrated using two real data sets: one with overdispersion, from smallmouth bass (Micropterus dolomieu), and the other without overdispersion, from rat (Rattus rattus). Article in Journal/Newspaper Rattus rattus Queensland University of Technology: QUT ePrints Canadian Journal of Fisheries and Aquatic Sciences 53 11 2533 2539 |
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Open Polar |
collection |
Queensland University of Technology: QUT ePrints |
op_collection_id |
ftqueensland |
language |
unknown |
topic |
likelihood-estimation recapture fish |
spellingShingle |
likelihood-estimation recapture fish Wang, Y-G. Loneragan, N. R. An extravariation model for improving confidence intervals of population size estimates from removal data |
topic_facet |
likelihood-estimation recapture fish |
description |
We propose a new model for estimating the size of a population from successive catches taken during a removal experiment. The data from these experiments often have excessive variation, known as overdispersion, as compared with that predicted by the multinomial model. The new model allows catchability to vary randomly among samplings, which accounts for overdispersion. When the catchability is assumed to have a beta distribution, the likelihood function, which is refered to as beta-multinomial, is derived, and hence the maximum likelihood estimates can be evaluated. Simulations show that in the presence of extravariation in the data, the confidence intervals have been substantially underestimated in previous models (Leslie-DeLury, Moran) and that the new model provides more reliable confidence intervals. The performance of these methods was also demonstrated using two real data sets: one with overdispersion, from smallmouth bass (Micropterus dolomieu), and the other without overdispersion, from rat (Rattus rattus). |
format |
Article in Journal/Newspaper |
author |
Wang, Y-G. Loneragan, N. R. |
author_facet |
Wang, Y-G. Loneragan, N. R. |
author_sort |
Wang, Y-G. |
title |
An extravariation model for improving confidence intervals of population size estimates from removal data |
title_short |
An extravariation model for improving confidence intervals of population size estimates from removal data |
title_full |
An extravariation model for improving confidence intervals of population size estimates from removal data |
title_fullStr |
An extravariation model for improving confidence intervals of population size estimates from removal data |
title_full_unstemmed |
An extravariation model for improving confidence intervals of population size estimates from removal data |
title_sort |
extravariation model for improving confidence intervals of population size estimates from removal data |
publisher |
National Research Council Canada |
publishDate |
1996 |
url |
https://eprints.qut.edu.au/90492/ |
genre |
Rattus rattus |
genre_facet |
Rattus rattus |
op_source |
Canadian Journal of Fisheries and Aquatic Sciences |
op_relation |
doi:10.1139/cjfas-53-11-2533 Wang, Y-G. & Loneragan, N. R. (1996) An extravariation model for improving confidence intervals of population size estimates from removal data. Canadian Journal of Fisheries and Aquatic Sciences, 53(11), pp. 2533-2539. https://eprints.qut.edu.au/90492/ Science & Engineering Faculty |
op_rights |
Consult author(s) regarding copyright matters This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au |
op_doi |
https://doi.org/10.1139/cjfas-53-11-2533 |
container_title |
Canadian Journal of Fisheries and Aquatic Sciences |
container_volume |
53 |
container_issue |
11 |
container_start_page |
2533 |
op_container_end_page |
2539 |
_version_ |
1788701129121464320 |