Condition-index based new ridge regression estimator for linear regression model with multicollinearity

Article Statistics & Probability

Quantile-based robust ridge m-estimator for linear regression model in presence of multicollinearity and outliers

Muhammad Suhail et al.

Summary: Two new robust quantile-based ridge estimators, QR and QRM, are proposed in this article to deal with outliers and multicollinearity in linear regression models. A simulation study shows that these estimators outperform other considered estimators based on mean square error criterion. An application is provided to demonstrate the performance of the proposed estimators.

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION (2021)

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Article Computer Science, Interdisciplinary Applications

Are most proposed ridge parameter estimators skewed and do they have any effect on MSE values?

Selman Mermi et al.

Summary: This study compared the ridge regression estimators encountered in the literature in terms of their distributions and Mean Square Error (MSE) values. It found that most ridge parameters exhibit skewed distributions, with only a few behaving like the Gauss distribution, and few ridge parameters distributed within the zero to ten range.

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION (2021)

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Article Multidisciplinary Sciences

Modified Liu estimators in the linear regression model: An application to Tobacco data

Iqra Babar et al.

Summary: This study proposes new estimators for shrinkage parameter in the context of multiple linear regression models with multicollinearity. The new estimators outperform existing ones in scenarios with high and severe multicollinearity. The empirical application using tobacco dataset supports the superiority of the new estimators.

PLOS ONE (2021)

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Article Multidisciplinary Sciences

Performance of Some New Ridge Parameters in Two-Parameter Ridge Regression Model

Seyab Yasin et al.

Summary: This article proposes new estimators for the ridge parameter to address the issue of multicollinearity, showing better performance in simulation studies, especially for high multicollinearity scenarios. The new estimators are also effective for some non-normal error distributions.

IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY TRANSACTION A-SCIENCE (2021)

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Article Statistics & Probability