Estimation of Growth Curves of Awassi Sheep by Isotonic Regression Analysis

Abstract

This study used isotonic regression analysis to classify non-linear regression models that were used to describe the growth curve in relation to different quality fit criteria. The best model selection was made by using the weight–age data obtained from Awassi sheep. Ten non-linear models measured by the fit quality determination coefficient, Akaike information criterion, Bayesian information criterion, mean quadratic estimation error, and estimated coefficient of determination were used. As a result of different non-linear models that were used to predict the growth curves of Awassi sheep and the isotonic regression analysis applied to these models, considering the Mean Square Error and R2 values, the Von Bertalanffy model turned out to be the most appropriate model. As a result, it was revealed that the percentage of predictability and goodness of fit of the models increased significantly with isotonic regression analysis, and as a result, more consistent adult weight estimations could be made.