THE EFFECT OF A FEATURE OF REGRESSION DISTURBANCE ON THE EFFICIENCY OF FITTING GROWTH-CURVES

Growth curve parameters are usually estimated by employing non-linear regression. In the present study this method was found to be inefficie nt for fitting growth curves, since the magnitude of random deviations of body weight greatly increases with age (hetemskedastic regression disturbance). Simulated samples of broiler body weights at different a ges were generated and the associated Gompertz growth curve parameters were estimated employing three methods. Comparison of the efficiency of these methods in fitting Gompertz growth curve under this regressio n disturbance were performed. The results indicate that the most effic ient method to estimate growth curve parameters is ''weighted nonlinea r regression''. The efficiency of this method was found to be much hig her than that of conventional non-linear regression. These findings sh ould be taken into consideration when fitting growth curves, in genera l, as well as for the Gompertz equation.