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Estimating Equations for Parameters in Stochastic Growth Models from Tag–Recapture Data
Author(s) -
Wang YouGan
Publication year - 1999
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.1999.00900.x
Subject(s) - mark and recapture , econometrics , statistics , growth curve (statistics) , mathematics , growth model , least squares function approximation , stochastic modelling , computer science , population , demography , mathematical economics , estimator , sociology
Summary. James (1991, Biometrics 47 , 1519–1530) constructed unbiased estimating functions for estimating the two parameters in the von Bertalanffy growth curve from tag‐recapture data. This paper provides unbiased estimating functions for a class of growth models that incorporate stochastic components and explanatory variables. A simulation study using seasonal growth models indicates that the proposed method works well while the least‐squares methods that are commonly used in the literature may produce substantially biased estimates. The proposed model and method are also applied to real data from tagged rock lobsters to assess the possible seasonal effect on growth.