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September 2016 Quantile sensitivity estimation for dependent sequences
Guangxin Jiang, Michael C. Fu
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J. Appl. Probab. 53(3): 715-732 (September 2016).

Abstract

In this paper we estimate quantile sensitivities for dependent sequences via infinitesimal perturbation analysis, and prove asymptotic unbiasedness, weak consistency, and a central limit theorem for the estimators under some mild conditions. Two common cases, the regenerative setting and ϕ-mixing, are analyzed further, and a new batched estimator is constructed based on regenerative cycles for regenerative processes. Two numerical examples, the G/G/1 queue and the Ornstein–Uhlenbeck process, are given to show the effectiveness of the estimator.

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Guangxin Jiang. Michael C. Fu. "Quantile sensitivity estimation for dependent sequences." J. Appl. Probab. 53 (3) 715 - 732, September 2016.

Information

Published: September 2016
First available in Project Euclid: 13 October 2016

zbMATH: 1351.62109
MathSciNet: MR3570090

Subjects:
Primary: 62H12
Secondary: 65C05

Keywords: Monte Carlo simulation , quantile , Regenerative process , sensitivity analysis , ϕ-mixing

Rights: Copyright © 2016 Applied Probability Trust

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Vol.53 • No. 3 • September 2016
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