Density estimation using bootstrap quantile variance and quantile-mean covariance

We evaluate two density estimators based on the quantile variance and quantile-mean covariance estimated by bootstrap. review previous developments estimation related to quantiles. Monte Carlo simulations for different data generating processes, sample sizes, other parameters show that perform well in comparison benchmark non-parametric kernel estimator. Some of explored smoothing techniques present lower bias mean integrated squared errors, which indicates proposed estimator is a promising strategy.