Large deviation estimates for exceedance times of perpetuity sequences and their dual processes

IF 2.1 1区 数学 Q1 STATISTICS & PROBABILITY
D. Buraczewski, Jeffrey F. Collamore, E. Damek, J. Zienkiewicz
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引用次数: 26

Abstract

In a variety of problems in pure and applied probability, it is relevant to study the large exceedance probabilities of the perpetuity sequence Yn:=B1+A1B2+⋯+(A1⋯An−1)BnYn:=B1+A1B2+⋯+(A1⋯An−1)Bn, where (Ai,Bi)⊂(0,∞)×R(Ai,Bi)⊂(0,∞)×R. Estimates for the stationary tail distribution of {Yn}{Yn} have been developed in the seminal papers of Kesten [Acta Math. 131 (1973) 207–248] and Goldie [Ann. Appl. Probab. 1 (1991) 126–166]. Specifically, it is well known that if M:=supnYnM:=supnYn, then P{M>u}∼CMu−ξP{M>u}∼CMu−ξ as u→∞u→∞. While much attention has been focused on extending such estimates to more general settings, little work has been devoted to understanding the path behavior of these processes. In this paper, we derive sharp asymptotic estimates for the normalized first passage time Tu:=(logu)−1inf{n:Yn>u}Tu:=(log⁡u)−1inf{n:Yn>u}. We begin by showing that, conditional on {Tu<∞}{Tu<∞}, Tu→ρTu→ρ as u→∞u→∞ for a certain positive constant ρρ. We then provide a conditional central limit theorem for {Tu}{Tu}, and study P{Tu∈G}P{Tu∈G} as u→∞u→∞ for sets G⊂[0,∞)G⊂[0,∞). If G⊂[0,ρ)G⊂[0,ρ), then we show that P{Tu∈G}uI(G)→C(G)P{Tu∈G}uI(G)→C(G) as u→∞u→∞ for a certain large deviation rate function II and constant C(G)C(G). On the other hand, if G⊂(ρ,∞)G⊂(ρ,∞), then we show that the tail behavior is actually quite complex and different asymptotic regimes are possible. We conclude by extending our results to the corresponding forward process, understood in the sense of Letac [In Random Matrices and Their Applications (Brunswick, Maine, 1984) (1986) 263–273 Amer. Math. Soc.], namely to the reflected process M∗n:=max{AnM∗n−1+Bn,0}Mn∗:=max{AnMn−1∗+Bn,0}, n∈Z+n∈Z+. Using Siegmund duality, we relate the first passage times of {Yn}{Yn} to the finite-time exceedance probabilities of {M∗n}{Mn∗}, yielding a new result concerning the convergence of {M∗n}{Mn∗} to its stationary distribution.
永续序列超越次数的大偏差估计及其对偶过程
在纯概率论和应用概率论的各种问题中,研究永续序列Yn:=B1+A1B2+⋯+(A1⋯An−1)BnYn:=B1+A1B2+⋯+(A1⋯An−1)Bn的大超越概率是相关的,其中(Ai,Bi)∧(0,∞)×R(Ai,Bi)∧(0,∞)×R。{Yn}{Yn}的平稳尾分布估计已经在Kesten[数学学报,131(1973)207-248]和Goldie [Ann. cn]的开创性论文中得到了发展。达成。约1(1991)126-166]。具体来说,众所周知,如果M:=supnYnM:=supnYn,则P{M>u}∼CMu−ξP{M>u}∼CMu−ξ为u→∞u→∞。虽然很多注意力都集中在将这种估计扩展到更一般的设置上,但很少有工作致力于理解这些过程的路径行为。本文给出了归一化首次通过时间Tu:=(logu) - 1inf{n:Yn>u}Tu:=(log u) - 1inf{n:Yn>u}的尖锐渐近估计。我们首先证明,在{Tu<∞}{Tu<∞}条件下,对于某正常数ρρ, Tu→ρ→u→∞为u→∞。然后,我们为{Tu}{Tu}提供一个条件中心极限定理,并研究P{Tu∈G}P{Tu∈G}对于集合G∧[0,∞]G∧[0,∞],作为u→∞u→∞。若G∧[0,ρ)G∧[0,ρ),则我们证明P{Tu∈G}uI(G)→C(G)P{Tu∈G}uI(G)→C(G)对于某大偏差率函数II和常数C(G), u→∞u→∞。另一方面,如果G∧(ρ,∞)G∧(ρ,∞),则我们证明了尾部行为实际上是相当复杂的,并且可能存在不同的渐近区域。最后,我们将我们的结果扩展到相应的前向过程,在Letac [in Random Matrices and Their Applications (Brunswick, Maine, 1984) (1986) 263-273 Amer]的意义上理解。数学。Soc。],即M∗n:=max{AnM∗n−1+Bn,0}Mn∗:=max{AnMn−1∗+Bn,0}, n∈Z+n∈Z+。利用Siegmund对偶性,我们将{Yn}{Yn}的第一次通过时间与{M∗n}{Mn∗}的有限时间超越概率联系起来,得到了关于{M∗n}{Mn∗}收敛于平稳分布的一个新结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Annals of Probability
Annals of Probability 数学-统计学与概率论
CiteScore
4.60
自引率
8.70%
发文量
61
审稿时长
6-12 weeks
期刊介绍: The Annals of Probability publishes research papers in modern probability theory, its relations to other areas of mathematics, and its applications in the physical and biological sciences. Emphasis is on importance, interest, and originality – formal novelty and correctness are not sufficient for publication. The Annals will also publish authoritative review papers and surveys of areas in vigorous development.
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