New Modified Liu Estimators to Handle the Multicollinearity in the Beta Regression Model: Simulation and Applications Article Swipe

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Ali Hammad , E. H. Hafez , Usman Shahzad , Elif Yıldırım , Ehab M. Almetwally , B. M. Golam Kibria ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.64389/mjs.2025.01111

The beta regression model (BRM) is widely used for analyzing bounded response variables, such as proportions, percentages. However, when multicollinearity exists among explanatory variables, the conventional maximum likelihood estimator (MLE) becomes unstable and inefficient. To address this issue, we propose new modified Liu estimators for the BRM, designed to enhance estimation accuracy in the presence of high multicollinearity among predictors. The proposed estimators extend the traditional Liu estimator by incorporating flexible biasing parameters, offering a more robust alternative to the MLE. Theoretical comparisons demonstrate the superiority of the new estimators over existing methods. Additionally, Monte Carlo simulations and real-world applications evidence their improved performance in terms of mean squared error (MSE) and mean absolute error (MAE). The results indicate that the proposed estimators significantly reduce estimation bias and variance under multicollinearity, providing more reliable regression coefficients.

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Multicollinearity Estimator Statistics Regression analysis Variance inflation factor Econometrics Computer science BETA (programming language) Mathematics Programming language

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Type: article
Language: en
Landing Page: https://doi.org/10.64389/mjs.2025.01111
PDF: https://sphinxsp.org/journal/index.php/mjs/article/download/11/11
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Cited By: 11
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DOI: https://doi.org/10.64389/mjs.2025.01111

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Title: New Modified Liu Estimators to Handle the Multicollinearity in the Beta Regression Model: Simulation and Applications

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Language: en

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Publication year: 2025

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Publication date: 2025-07-12

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Authors: Ali Hammad, E. H. Hafez, Usman Shahzad, Elif Yıldırım, Ehab M. Almetwally, B. M. Golam Kibria

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Landing page: https://doi.org/10.64389/mjs.2025.01111

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Concepts: Multicollinearity, Estimator, Statistics, Regression analysis, Variance inflation factor, Econometrics, Computer science, BETA (programming language), Mathematics, Programming language

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Cited by: 11

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