Density functions for QuickQuant and QuickVal

arxiv(2023)

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摘要
We prove that, for every 0 < t < 1, the limiting distribution of the scale-normalized number of key comparisons used by the celebrated algorithm QuickQuant to find the tth quantile in a randomly ordered list has a Lipschitz continuous density function ft that is bounded above by 10. Furthermore, this density ft(x) is positive for every x > min{t, 1-t} and, uniformly in t, enjoys superexponential decay in the right tail. We also prove that the survival function 1 - Ft(x) = fx infinity ft(y) dy and the density function ft(x) both have the right tail asymptotics exp[-x ln x - x ln ln x + O(x)]. We use the right-tail asymptotics to bound large deviations for the scale-normalized number of key comparisons used by QuickQuant.
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关键词
QuickQuant,QuickSelect,QuickVal,searching,convolutions of distributions,den-sities,integral equations,asymptotic bounds,tails of distributions,tails of densities,large deviations,moment generating functions,Lipschitz continuity,perfect simulation
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