A New Robust LQS-NTP Estimator for Mitigating Correlated Endogenous Variables and Extreme Observations in Linear Regression Models: Theoretical Development and Applications
This study proposes a Robust Least Quantile of Squares–New Two-Parameter (LQS-NTP) estimator for addressing multicollinearity and extreme observations in linear regression models. The proposed estimator combines the high-breakdown robustness of the Least Quantile of Squares (LQS) method with the shrinkage properties of...