A note on estimating cumulative distribution functions by the use of convolution power kernels

Our paper investigates the nonparametric estimation of cumulative distribution functions of nonnegative valued random variables using convolution power kernels. Our proposed consistent estimator avoids boundary effects near the origin. We present its asymptotic properties and give a short simulation study.