Article ID Journal Published Year Pages File Type
5129790 Statistics & Probability Letters 2017 9 Pages PDF
Abstract

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.

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Related Topics
Physical Sciences and Engineering Mathematics Statistics and Probability
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A note on estimating cumulative distribution functions by the use of convolution power kernels
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