Technical Note—On Estimating Quantile Sensitivities via Infinitesimal Perturbation Analysis
Operations Research · 2015 · Volume 63 · Issue 2
Abstract
Hong (2009) [Hong LJ (2009) Estimating quantile sensitivities. Oper. Res. 57(1):118-130.] introduced a general framework based on probability sensitivities and a conditional expectation relationship for estimating quantile sensitivities by infinitesimal perturbation analysis (IPA). We present an alternative more direct derivation of the IPA estimators that leads to simplified proofs for strong consistency and convergence rate of the unbatched estimator, and strong consistency and a central limit theorem for the batched estimator.
Keywords
quantile, gradient estimation, Monte Carlo simulation, sensitivity analysis
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