The article discusses a new method for analyzing data that has varying levels of uncertainty. Instead of using a fully nonparametric approach, the researchers propose a more efficient way to model this uncertainty by combining parametric and nonparametric elements. This method allows for better estimation of certain components in the data, leading to more accurate results. The researchers tested their approach on a dataset about gasoline consumption and found it to be effective in improving estimation accuracy.