Comparing Predictive Performances of some Nonlinear Functions and Multivariate Adaptive Regression Splines (MARS) for Describing the Growth of Daera Dın Panah (DDP) Goat in Pakistan
Comparing Predictive Performances of some Nonlinear Functions and Multivariate Adaptive Regression Splines (MARS) for Describing the Growth of Daera Dın Panah (DDP) Goat in Pakistan
Senol Celik1,*, Ecevit Eyduran2, Adile Tatliyer3, Koksal Karadas4, Mehmet Kazim Kara2 and Abdul Waheed5
ABSTRACT
This study was conducted to evaluate the most suitable nonlinear functions amongst Morgan-Mercer-Flodin (MMF), Logistic, Von-Bertalanffy and Janosheck models, based on monthly records of body weight from birth to 1 year in Daera Din Panah (DDP) goat. Based on coefficient of determination (R2), adjusted coefficient of determination (R2ADJUSTED) and root mean square error (RMSE) were used. Janosheck model was chosen as the most appropriate model for its highest R2 (0.999) and smallest RMSE (0.124). Growth related parameters (A, B, k, and d) of the Janoscheck non-linear model were estimated as 43.000, 0.905, 0.124 and 0.950, respectively. To conclude, it could be suggested that the Janoscheck non-linear model might help breeders who aim to make precise decisions on optimum slaughtering time and to ensure suitable managerial conditions in DDP goat.
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June 2018
Vol. 50, Iss. 3, Pages 799-1198
