Marshall lemma in discrete convex estimation

Statistics & Probability Letters（2015）

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摘要

We show that the supremum distance between the cumulative distribution of the convex LSE and an arbitrary distribution function F with a convex pmf on N is at most twice the supremum distance between the empirical distribution function and F.

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关键词

Convex,Nonparametric least squares,Marshall lemma,pmf,Shape constraints

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