Dimension test approach of heteroscedasticity in the linear model. Issue 6 (3rd July 2017)

• Record Type: Journal Article
• Authors: Lee, Keunbaik; Song, Hyejin; Yoo, Jae Keun
• Is Part Of: Communications in statistics. Volume 46:Issue 6(2017)
• Page Start: 4356
• Page End: 4366
• Publication Date: 2017-07-03
• Subjects: Heteroscedasticity -- Linear model -- Permutation test -- Sliced average variance estimation; 62G08 -- 62H05; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2015.1117636
• Languages: English
• ISSNs: 0361-0918

Abstract

ABSTRACT: Heteroscedasticity testing has a long history and is still an important matter in the linear model. There exist many types of tests, but they are limited in use to their own specific cases and sensitive to normality. Here, we propose a dimension test approach to heteroscedasticity. The proposed test overcomes the shortcomings of the existing methods, so that it is robust to normality and is unified in sense that it is applicable in the linear model with multi-dimensional response. Numerical studies confirm that the proposed test is favorable over the existing tests with moderate sample sizes, and real data analysis is presented.