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

Home Page
About
Submit A Journal
Submit A Conference
Submit Paper/Book
- Submit a Preprint
- Submit a Book
Contact

Hacettepe Journal of Mathematics and Statistics
Volume:50 Issue:6
A computational approach test for comparing two linear regression models with unequal variances

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

Authors : Mehmet YAZICI, Fikri GÖKPINAR, Esra GÖKPINAR, Meral EBEGİL, Yaprak ÖZDEMİR

Pages : 1756-1772

Doi:10.15672/hujms.784623

View : 25 | Download : 9

Publication Date : 2021-12-14

Article Type : Research Paper

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

ORIGINAL ARTICLE URL

VIEW PAPER (PDF)

* There may have been changes in the journal, article,conference, book, preprint etc. informations. Therefore, it would be appropriate to follow the information on the official page of the source. The information here is shared for informational purposes. IAD is not responsible for incorrect or missing information.