ON CONVERGENCE TO STATIONARITY OF FRACTIONAL BROWNIAN STORAGE

被引:9
|
作者
Mandjes, Michel [1 ,2 ]
Norros, Ilkka [3 ]
Glynn, Peter [2 ]
机构
[1] Korteweg de Vries Inst Math, NL-1018 TV Amsterdam, Netherlands
[2] Stanford Univ, Stanford, CA 94305 USA
[3] VTT Informat Technol, Espoo, Finland
来源
ANNALS OF APPLIED PROBABILITY | 2009年 / 19卷 / 04期
关键词
Convergence to stationarity; fractional Brownian motion; storage process; large deviations; PATH LARGE DEVIATIONS; SINGLE-SERVER QUEUE; GAUSSIAN-PROCESSES; OVERFLOW PROBABILITIES; INPUT; ASYMPTOTICS; NETWORKS;
D O I
10.1214/08-AAP578
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
With M(t) := sup(s is an element of[0,t]) A(s) - s denoting the running maximum of a fractional Brownian motion A(.) with negative drift, this paper studies the rate of convergence of P(M(t) > x) to P(M > x). We define two metrics that measure the distance between the (complementary) distribution functions P(M(t) > .) and P(M > .). Our main result states that both metrics roughly decay as exp(-vt(2-2H)), where v is the decay rate corresponding to the tail distribution of the busy period in an fBm-driven queue, which was computed recently [23] The proofs extensively rely on application of the well-known large deviations theorem for Gaussian processes. We also show that the identified relation between the decay of the convergence metrics and busy-period asymptotics holds in other settings as well, most notably when Gartner-Ellis-type conditions are fulfilled.
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页码:1385 / 1403
页数:19
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