What question did this study set out to answer?

This research aims to compare the performance of Ridge regression and Reciprocal Lasso estimators in semiparametric additive partial linear models under multicollinearity conditions.

January 20, 2026Open Access

A Comparative Study of Ridge Robust and Reciprocal Lasso Estimators for Semiparametric Additive Partial Linear Models Under Multicollinearity

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Authors

HTHayder Raaid TalibThi Qar University NFNoor Abdul-Kareem FayadhThi Qar University SASarah Sabah Akram

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Implication

Comparative analysis reveals Reciprocal Lasso offers better predictions in multicollinearity contexts, suggesting improved variable selection.

Key Points

This research aims to compare the performance of Ridge regression and Reciprocal Lasso estimators in semiparametric additive partial linear models under multicollinearity conditions.
Compared Ridge regression with R/W robust estimators and Reciprocal Lasso method.
Evaluated three criteria: Average Absolute Deviation Error (AADE), Mean Squared Error (MSE), and coefficient of determination (R2).
Utilized educational data on factors affecting academic performance of special needs students.
Reciprocal Lasso provided more accurate predictions and better variable selection than Ridge methods.
The Lasso method was favored when the sample size was smaller than the number of variables.
The Ridge with W robust method worked best with moderate correlations, while the Ridge with R robust method excelled in strong relationships.

Cite This Study

Talib et al. (2026) studied this question.

synapsesocial.com/papers/696f1a239e64f732b51ee6ae https://doi.org/10.19139/soic-2310-5070-3299

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Implication

Comparative analysis reveals Reciprocal Lasso offers better predictions in multicollinearity contexts, suggesting improved variable selection.

A Comparative Study of Ridge Robust and Reciprocal Lasso Estimators for Semiparametric Additive Partial Linear Models Under Multicollinearity

Discussion

Member takes

Implication

Key Points

Cite This Study

A Comparative Study of Ridge Robust and Reciprocal Lasso Estimators for Semiparametric Additive Partial Linear Models Under Multicollinearity

Discussion

Member takes

Implication

Key Points

Cite This Study

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