The sharp form of the Kolmogorov--Rogozin inequality and a conjecture of Leader--Radcliffe
Abstract
Let X be a random variable and define its concentration function by Qh(X)=x∈ RP(X∈ (x,x+h]). For a sum Sn=X1+·s+Xn of independent real-valued random variables the Kolmogorov-Rogozin inequality states that Qh(Sn)≤ C(Σi=1n(1-Qh(Xi)))-12. In this paper we give an optimal bound for Qh(Sn) in terms of Qh(Xi), which settles a question posed by Leader and Radcliffe in 1994. Moreover, we show that the extremal distributions are mixtures of two uniform distributions each lying on an arithmetic progression.
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