The article discusses how to estimate a type of regression model with varying error amounts. The researchers looked at using wavelet estimators to find the slope and nonparametric parts of the model when the error variance is known. They also studied how to estimate these parts when the error variance is unknown. Their findings show that the estimators are likely to be normally distributed under certain conditions. A simulation study was conducted to show that their theoretical results are practical.