Nonparametric density estimation based on the scaled Laplace transform inversion

Abstract

New nonparametric procedure for estimating the probability density function of a positive random variable is suggested. Asymptotic expressions of the bias term and Mean Squared Error are derived. By means of graphical illustrations and evaluating the Average of L2-errors we conducted comparisons of the finite sample performance of proposed estimate with the one based on kernel density method.