Generalized linear models, generalized additive models and generalized estimating equations to capture-recapture closed population models
Main Author: | |
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Publication Date: | 2014 |
Other Authors: | |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10174/13864 |
Summary: | Estimation of animal population parameters is an important issue in ecological statistics. In this paper generalized linear models (GLM), generalized additive models (GAM) and generalized estimating equations (GEE) are used to account for individual heterogeneity, modelling capture probabilities as a function of individual observed covariates. The GEE also accounts for a correlation structure among capture occasions. We are interested in estimating closed population size, where only heterogeneity is considered, there is no time e ect or behavioral response to capture, and the capture probabilities depend on covariates. A real example is used for illustrative purposes. Conditional arguments are used to obtain a Horvitz-Thompson-like estimator for estimating population size. A simulation study is also conducted to show the performance of the estimation procedure and for comparison between methodologies. The GEE approach performs better than GLM or GAM approaches for estimating population size. The simulation study highlight the importance of considering correlation among capture occasions. |
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Generalized linear models, generalized additive models and generalized estimating equations to capture-recapture closed population modelsCapture-recapture ExperimentGeneralized linear modelsGeneralized additive modelsGeneralized linear mixed modelsGeneralized estimating equationsPopulation size estimationEstimation of animal population parameters is an important issue in ecological statistics. In this paper generalized linear models (GLM), generalized additive models (GAM) and generalized estimating equations (GEE) are used to account for individual heterogeneity, modelling capture probabilities as a function of individual observed covariates. The GEE also accounts for a correlation structure among capture occasions. We are interested in estimating closed population size, where only heterogeneity is considered, there is no time e ect or behavioral response to capture, and the capture probabilities depend on covariates. A real example is used for illustrative purposes. Conditional arguments are used to obtain a Horvitz-Thompson-like estimator for estimating population size. A simulation study is also conducted to show the performance of the estimation procedure and for comparison between methodologies. The GEE approach performs better than GLM or GAM approaches for estimating population size. The simulation study highlight the importance of considering correlation among capture occasions.Sociedade Portuguesa de Estatística2015-03-31T10:43:56Z2015-03-312014-12-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/13864http://hdl.handle.net/10174/13864engAkanda, Md.A.S, Alpizar-Jara. (2014). Generalized linear models, generalized additive models and generalized estimating equations to capture-recapture closed population models. In Estatística: A ciência da incerteza. Atas do XXI Congresso Anual da Sociedade Portuguesa de Estatística. (Eds. Pereira, I., Freitas, A., Scotto, M., Silva, M. E., Paulino, C. D.). Edições SPE, 169-181.978-972-8890-35-3ndalpizar@uevora.pt336Akanda, Md. Abdus SalamAlpizar-Jara, Russellinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-01-03T18:59:44Zoai:dspace.uevora.pt:10174/13864Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T12:05:45.137534Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Generalized linear models, generalized additive models and generalized estimating equations to capture-recapture closed population models |
title |
Generalized linear models, generalized additive models and generalized estimating equations to capture-recapture closed population models |
spellingShingle |
Generalized linear models, generalized additive models and generalized estimating equations to capture-recapture closed population models Akanda, Md. Abdus Salam Capture-recapture Experiment Generalized linear models Generalized additive models Generalized linear mixed models Generalized estimating equations Population size estimation |
title_short |
Generalized linear models, generalized additive models and generalized estimating equations to capture-recapture closed population models |
title_full |
Generalized linear models, generalized additive models and generalized estimating equations to capture-recapture closed population models |
title_fullStr |
Generalized linear models, generalized additive models and generalized estimating equations to capture-recapture closed population models |
title_full_unstemmed |
Generalized linear models, generalized additive models and generalized estimating equations to capture-recapture closed population models |
title_sort |
Generalized linear models, generalized additive models and generalized estimating equations to capture-recapture closed population models |
author |
Akanda, Md. Abdus Salam |
author_facet |
Akanda, Md. Abdus Salam Alpizar-Jara, Russell |
author_role |
author |
author2 |
Alpizar-Jara, Russell |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Akanda, Md. Abdus Salam Alpizar-Jara, Russell |
dc.subject.por.fl_str_mv |
Capture-recapture Experiment Generalized linear models Generalized additive models Generalized linear mixed models Generalized estimating equations Population size estimation |
topic |
Capture-recapture Experiment Generalized linear models Generalized additive models Generalized linear mixed models Generalized estimating equations Population size estimation |
description |
Estimation of animal population parameters is an important issue in ecological statistics. In this paper generalized linear models (GLM), generalized additive models (GAM) and generalized estimating equations (GEE) are used to account for individual heterogeneity, modelling capture probabilities as a function of individual observed covariates. The GEE also accounts for a correlation structure among capture occasions. We are interested in estimating closed population size, where only heterogeneity is considered, there is no time e ect or behavioral response to capture, and the capture probabilities depend on covariates. A real example is used for illustrative purposes. Conditional arguments are used to obtain a Horvitz-Thompson-like estimator for estimating population size. A simulation study is also conducted to show the performance of the estimation procedure and for comparison between methodologies. The GEE approach performs better than GLM or GAM approaches for estimating population size. The simulation study highlight the importance of considering correlation among capture occasions. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-12-01T00:00:00Z 2015-03-31T10:43:56Z 2015-03-31 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/13864 http://hdl.handle.net/10174/13864 |
url |
http://hdl.handle.net/10174/13864 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Akanda, Md.A.S, Alpizar-Jara. (2014). Generalized linear models, generalized additive models and generalized estimating equations to capture-recapture closed population models. In Estatística: A ciência da incerteza. Atas do XXI Congresso Anual da Sociedade Portuguesa de Estatística. (Eds. Pereira, I., Freitas, A., Scotto, M., Silva, M. E., Paulino, C. D.). Edições SPE, 169-181. 978-972-8890-35-3 nd alpizar@uevora.pt 336 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Sociedade Portuguesa de Estatística |
publisher.none.fl_str_mv |
Sociedade Portuguesa de Estatística |
dc.source.none.fl_str_mv |
reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
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RCAAP |
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RCAAP |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
repository.mail.fl_str_mv |
info@rcaap.pt |
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