Sampling at a random time with a heavy-tailed distribution (Q2708441)
From MaRDI portal
| This is the item page for this Wikibase entity, intended for internal use and editing purposes. Please use this page instead for the normal view: Sampling at a random time with a heavy-tailed distribution |
scientific article
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Sampling at a random time with a heavy-tailed distribution |
scientific article |
Statements
17 January 2002
0 references
Little's law
0 references
subexponential distribution
0 references
GI/G/1 queue
0 references
0.8643012
0 references
0.85497344
0 references
0.85247386
0 references
0.85129285
0 references
0.84885037
0 references
0.84885037
0 references
0.84284127
0 references
Sampling at a random time with a heavy-tailed distribution (English)
0 references
Let \(\{X(t)\}\) be a renewal process with epochs \(S_n\) and \(T\) an independent heavy-tailed random variable. The asymptotics of \(P(X(T)> n)\), \(n\to\infty\), and more generally of \(Ee^{-g(S_n)}\) is studied as \(n\to\infty\), thereby extending \textit{S. Asmussen}, \textit{C. Klüppelberg} and \textit{K. Sigman} [Stochastic Processes Appl. 79, No. 2, 265-286 (1999; Zbl 0961.60080)] who dealt with the Poisson case. As in the quoted paper two different scenarios emerge according to whether \(\log P(T> t)\) decreases slower (as in the regularly varying case) or faster than \(-\sqrt t\). Applications to the GI/G/1 queue are given. The proofs rely heavily upon large deviations techniques.
0 references