
doi: 10.1017/jpr.2016.36
AbstractIn 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.
65C05, Estimation in multivariate analysis, Monte Carlo methods, ϕ-mixing, regenerative process, quantile, sensitivity analysis, \(\phi\)-mixing, 62H12, Quantile, Monte Carlo simulation
65C05, Estimation in multivariate analysis, Monte Carlo methods, ϕ-mixing, regenerative process, quantile, sensitivity analysis, \(\phi\)-mixing, 62H12, Quantile, Monte Carlo simulation
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