محمود افشاری

One of the most important issues in statistics has been determine of an appropriate estimation for statistical functions, so,one of the main statistical functions is a density function. The overall purpose of this thesis is non-parametric estimation of the density function f(x) based on a wavelet method,and also, evaluation of the biased risk and right censoring. The first chapter of this thesis includes wavelet definition and related terms. In the second chapter introducing the censored data and we estimate the density function in different ways. In the third, we have non-parametric density estimation in presence of bias and right censoring. In the last chapter, using simulations and practical, we obtain non-parametric estimation and hard treshold of the density function f(x) in presence of bias and right censored data by using wavelet method.