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

被引:1
|
作者
Yazici, Mehmet Enes [1 ]
Gokpinar, Fikri [2 ]
Gokpinar, Esra [2 ]
Ebegil, Meral [2 ]
ozdemir, Yaprak Arzu [2 ]
机构
[1] Social Secur Inst, Ankara, Turkey
[2] Gazi Univ, Dept Stat, Fac Sci, Ankara, Turkey
来源
关键词
  Chow test; computational approach test; parametric bootstrap test; heteroscedasticity regression models; DISTURBANCE VARIANCES; CHOW TEST; EQUALITY; COEFFICIENTS; SETS; INFERENCE; RATIO;
D O I
10.15672/hujms.784623
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
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 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 cases considered. Besides, an illustration of the proposed test was given by using a sample dataset.
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页码:1756 / 1772
页数:17
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