Comparison of Least Squares and Some Bias Estimators in Multicollinearity




Least squares method, Ridge regression, Principal component regression, Saanen, Multicolinearity


The aim of this study is to compare the least squares (LS) method that lost its function in the case of multicollinearity in regression methods with Ridge Regression (RR) and Principal Components Regression (PCR) which are bias estimators. For this aim, the effect of some body measurements on body weight (BW), body length (BL), height at withers (HW), height at rump (HR), chest depth (CD), chest girth (CG) and chest width (CW) obtained from 59 Saanen kids at weaning period raised at Research Farm of Tokat Gaziosmanpaşa University. Determination coefficient (R2) and mean square error (MSE) values were used to evaluate the estimation performance of the methods. The multicollinearity between height at withers (HW) and height at rump (HR) which were used to estimate body weight was eliminated by using RR and PCR. When R2 and HKO values of the examined methods are compared; It has been shown that RR method have better results of live weight of Saanen goats.



How to Cite

Yılmaz, F., Bayyurt, L., Abacı, S. H., & Tahtalı, Y. (2020). Comparison of Least Squares and Some Bias Estimators in Multicollinearity. Turkish Journal of Agriculture - Food Science and Technology, 8(3), 793–799.



Research Paper

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