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Journals / Hacettepe Journal of Mathematics and Statistics / 2021 / Cilt: 50 - Sayı: 6

A computational approach test for comparing two linear regression models with unequal variances

Fikri Gökpınar
Esra Gökpınar
Meral Ebegil
Yaprak Arzu Özdemir
Mehmet Enes Yazıcı
Pages
1756–1772
Publication Date
2022-10-18
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Besides, an illustration of the proposed test was given by using a sample dataset.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, a new testing procedure is proposed to compare two linear regression models based on a computational approach test when the variances are not assumed to be equal.
📊
Key Findings & Data:To assess performance of the proposed test, it was compared with some existing tests in terms of power and type I error rate of the test.
💡
Conclusion & Impact:Besides, an illustration of the proposed test was given by using a sample dataset.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Chow Test · Computational Approach Test · Parametric Bootstrap Test

Abstract

In this study, a new testing procedure is proposed to compare two linear regression models based on a computational approach test when the variances are not assumed to be equal. This method is based on restricted maximum likelihood estimators and some simple computational steps. To assess performance of the proposed test, it was compared with some existing tests in terms of power and type I error rate of the test. The simulation study reveals that the proposed test is a better alternative than some existing tests in most considered cases. Besides, an illustration of the proposed test was given by using a sample dataset.

🔖

Cite This Article

Gökpınar, F., Gökpınar, E., Ebegil, M., Özdemir, Y. A., Yazıcı, M. E. (2022). A computational approach test for comparing two linear regression models with unequal variances. Hacettepe Journal of Mathematics and Statistics, Cilt: 50 - Sayı: 6, 1756–1772. https://ajindex.com/articles/529466

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