Quasi-likelihood ratio tests for homoscedasticity in linear regression

Lili Yu; Varadan Sevilimedu; Robert Voge; Hani Samawi

doi:10.22237/JMASM/1556669460

Quasi-likelihood ratio tests for homoscedasticity in linear regression

Lili Yu, Varadan Sevilimedu, Robert Voge, Hani Samawi

Biostatistics, Epidemiology, & Environmental Health Sciences

Georgia Southern University

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Two quasi-likelihood ratio tests are proposed for the homoscedasticity assumption in the linear regression models. They require few assumptions than the existing tests. The properties of the tests are investigated through simulation studies. An example is provided to illustrate the usefulness of the new proposed tests.

Original language	English
Article number	9460
Pages (from-to)	1-16
Number of pages	16
Journal	Journal of Modern Applied Statistical Methods
Volume	18
Issue number	1
DOIs	https://doi.org/10.22237/JMASM/1556669460
State	Published - 2019

Keywords

Bootstrap
Homoscedasticity test
Quasi-likelihood
Regression model
Variance function

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10.22237/JMASM/1556669460

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title = "Quasi-likelihood ratio tests for homoscedasticity in linear regression",

abstract = "Two quasi-likelihood ratio tests are proposed for the homoscedasticity assumption in the linear regression models. They require few assumptions than the existing tests. The properties of the tests are investigated through simulation studies. An example is provided to illustrate the usefulness of the new proposed tests.",

keywords = "Bootstrap, Homoscedasticity test, Quasi-likelihood, Regression model, Variance function",

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KW - Bootstrap

KW - Homoscedasticity test

KW - Quasi-likelihood

KW - Regression model

KW - Variance function

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Quasi-likelihood ratio tests for homoscedasticity in linear regression

Abstract

Keywords

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