Homoscedasticity tests for both low and high-dimensional fixed design regressions
classification
🧮 math.ST
stat.TH
keywords
asymptoticcovariatesfixedhomoscedasticityinfinitynormalitytendswithout
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This paper is to prove the asymptotic normality of a statistic for detecting the existence of heteroscedasticity for linear regression models without assuming randomness of covariates when the sample size $n$ tends to infinity and the number of covariates $p$ is either fixed or tends to infinity. Moreover our approach indicates that its asymptotic normality holds even without homoscedasticity.
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