{ "id": "0908.4472", "version": "v1", "published": "2009-08-31T08:07:28.000Z", "updated": "2009-08-31T08:07:28.000Z", "title": "On convergence to stationarity of fractional Brownian storage", "authors": [ "Michel Mandjes", "Ilkka Norros", "Peter Glynn" ], "comment": "Published in at http://dx.doi.org/10.1214/08-AAP578 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)", "journal": "Annals of Applied Probability 2009, Vol. 19, No. 4, 1385-1403", "doi": "10.1214/08-AAP578", "categories": [ "math.PR" ], "abstract": "With $M(t):=\\sup_{s\\in[0,t]}A(s)-s$ denoting the running maximum of a fractional Brownian motion $A(\\cdot)$ with negative drift, this paper studies the rate of convergence of $\\mathbb {P}(M(t)>x)$ to $\\mathbb{P}(M>x)$. We define two metrics that measure the distance between the (complementary) distribution functions $\\mathbb{P}(M(t)>\\cdot)$ and $\\mathbb{P}(M>\\cdot)$. Our main result states that both metrics roughly decay as $\\exp(-\\vartheta t^{2-2H})$, where $\\vartheta$ is the decay rate corresponding to the tail distribution of the busy period in an fBm-driven queue, which was computed recently [Stochastic Process. Appl. (2006) 116 1269--1293]. 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 G\\\"artner--Ellis-type conditions are fulfilled.", "revisions": [ { "version": "v1", "updated": "2009-08-31T08:07:28.000Z" } ], "analyses": { "subjects": [ "60G15", "60G18", "90B05" ], "keywords": [ "fractional brownian storage", "convergence", "well-known large deviations theorem", "stationarity", "fractional brownian motion" ], "tags": [ "journal article" ], "note": { "typesetting": "TeX", "pages": 0, "language": "en", "license": "arXiv", "status": "editable", "adsabs": "2009arXiv0908.4472M" } } }