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Multicollinearity and Outliers in Logistic Regression by Elang Nugraha is a document available to read on EtoBox.

This article discusses the challenges of multicollinearity and outliers in logistic regression and introduces a robust estimator called the Kibria–Lukman estimator. The study evaluates various estimators, including the Bianco–Yohai and conditionally unbiased bounded influence estimators, through simulations and real-life examples, finding that KL-BY offers superior performance. The proposed method aims to improve prediction accuracy and stability in logistic regression models by addressing both multicolline

Author

Elang Nugraha

Language

EN