Asymptotics of the maximal radius of an LrL^r-optimal sequence of quantizers

preprint2012arXivOpen access

Abstract

Let PP be a probability distribution on Rd\mathbb{R}^d (equipped with an Euclidean norm ∣⋅∣|\cdot|). Let r>0 r> 0 and let (αn)n≥1(α_n)_{n \geq1} be an (asymptotically) Lr(P)L^r(P)-optimal sequence of nn-quantizers. We investigate the asymptotic behavior of the maximal radius sequence induced by the sequence (αn)n≥1(α_n)_{n \geq1} defined for every n≥1n \geq1 by ρ(αn)=max⁡∣a∣,a∈αnρ(α_n) = \max{|a|, a \inα_n}. When $\card(\supp(P))$ is infinite, the maximal radius sequence goes to sup⁡∣x∣,x∈supp⁡(P)\sup{|x|, x \in\operatorname{supp}(P)} as nn goes to infinity. We then give the exact rate of convergence for two classes of distributions with unbounded support: distributions with hyper-exponential tails and distributions with polynomial tails. In the one-dimensional setting, a sharp rate and constant are provided for distributions with hyper-exponential tails.

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