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

Year 2021, Volume: 50 Issue: 6, 1756 - 1772, 14.12.2021

Mehmet Yazıcı Fikri Gökpınar , Esra Gökpınar , Meral Ebegil , Yaprak Özdemir

https://doi.org/10.15672/hujms.784623

Cited By: 3

https://izlik.org/JA26JH74PH

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.

Keywords

Chow Test , Computational Approach Test , Parametric Bootstrap Test , Heteroscedasticity regression models

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