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Title: Generalized linear models, generalized additive models and generalized estimating equations to capture-recapture closed population models
Authors: Akanda, Md. Abdus Salam
Alpizar-Jara, Russell
Editors: Pereira, Isabel
Freitas, Adelaide
Scotto, Manuel
Silva, Maria Eduarda
Paulino, Carlos Daniel
Keywords: Capture-recapture Experiment
Generalized linear models
Generalized additive models
Generalized linear mixed models
Generalized estimating equations
Population size estimation
Issue Date: Dec-2014
Publisher: Sociedade Portuguesa de Estatística
Citation: 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.
Abstract: 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.
ISBN: 978-972-8890-35-3
Type: article
Appears in Collections:CIMA - Artigos em Livros de Actas/Proceedings

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