A comprehensive review of regression models under heteroscedasticity: research review
Heteroscedasticity is a common problem in linear regression analysis that can reduce the efficiency of ordinary least squares estimates, distort standard errors, and lead to unreliable statistical inference. This study aims to systematize the main approaches to detecting and correcting heteroscedasticity and to compare...