A two-stage fuzzy least squares procedure for fitting linearized von Bertalanffy growth model

摘要

In this paper, fitting of linearized von Bertalanffy growth model is revisited when response variabe is reported in intervals corresponding to various values of explanatory variable. Earlier, Tanka's linear programming methodology was used to handle this problem. However, this approach has several limitations, which are highlighted. Accordingly, a more efficient two stage procedure based on fuzzy least squares, is employed. The methodology is thoroughly discussed and, for its application, relevant computer programs are developed in "Nonlinear programming solver LINGO, Version 8" software package. Finally, an illustration to pearl oyster age-length data is discussed.