This paper considers several estimators for estimating the biasing parameter in the study of partial linear models in the presence of multicollinearity. After exhibiting the MSE of ridge estimator based on eigenvalues of design matrix, a simulation study has been conducted to compare the performance of the estimators. Based on the simulation study we found that, increasing the correlation between the independent variables has positive effect on the MSE (signal-to-noise-ratio). However, increasing the value of ρ has negative effect on MSE. When the sample size increases the MSE decreases even when the correlation between the independent variables is large. An application of the proposed model is considered for housing attributes to illustrate the performance of different estimators.

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