Bagging of density estimators

Mathias Bourel, Jairo Cugliari

Abstract: In this work we give new density estimators by averaging classical density estimators such as the histogram, the frequency polygon and the kernel density estimators obtained over different bootstrap samples of the original data. Using existent results, we prove the \(L^2\)-consistency of these new estimators and compare them to several similar approaches by simulations. Based on them, we give also a way to construct non-parametric pointwise variability band for the target density.