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Estimating equations for removal data analysis
Authors:Wang Y G
Institution:Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA. ygwang@hsph.harvard.edu
Abstract:We consider the problem of estimating a population size from successive catches taken during a removal experiment and propose two estimating functions approaches, the traditional quasi-likelihood (TQL) approach for dependent observations and the conditional quasi-likelihood (CQL) approach using the conditional mean and conditional variance of the catch given previous catches. Asymptotic covariance of the estimates and the relationship between the two methods are derived. Simulation results and application to the catch data from smallmouth bass show that the proposed estimating functions perform better than other existing methods, especially in the presence of overdispersion.
Keywords:Estimating functions  Fisher information  Likelihood  Martingale  Overdispersion  Removal data
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