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A statistical study of fish population dynamics using maximum likelihood method: Parameter estimation and model selection



A statistical study of fish population dynamics using maximum likelihood method: Parameter estimation and model selection



Bulletin of the National Research Institute of Far Seas Fisheries 0(29): 57-109



The data used in the fish population dynamics are often subject to considerable stochastic variations and measurement errors. It is necessary to use sound statistical techniques in the analysis of data. Although the linear least square method (linear regression) has been used in the estimation procedure, there are some disadvantages such as necessity of linearization and underlying assumption of normal distribution. Recently, there is increasing interest in the maximum likelihood method. However, the application of maximum likelihood method for fisheries science is still limited and the advantages of this method are not well known. In this paper, the estimation of stock-recruitment relationship, the determination of the mesh selectivity curve, the estimation of mortality rates from tag recoveries, and the DeLury method of estimating population abundance are studied using the maximum likelihood method. The advantages of maximum likelihood parameter estimation and model selection are shown through above examples. The traditional approaches are also discussed.

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Accession: 008078701

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