This work studies two different algorithms on non-parametric density estimators. The first algorithm, based on kernel density estimators, gives a method for approximating the optimal parameter The second algorithm studied works with variable kernel estimators finding for this estimator optimal parameters. Very good results were obtained with the samples studied, with the first algorithm. With the second one, several problems were found, with the implementation of the proposed algorithm as well as with the algorithm itself.