Nonhomogeneous Gaussian regression

Nonhomogeneous Gaussian regression is a statistical modeling technique that extends the standard Gaussian regression framework to handle situations where the variability of the response variable is not constant across the range of the predictor(s). In other words, it allows for the modeling of data where the variance of the errors depends on the levels of the predictor variables. In standard Gaussian regression, we typically assume that the errors (or residuals) are normally distributed and have constant variance (homoscedasticity).