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.
| Original language | English |
|---|---|
| Pages (from-to) | 435-441 |
| Number of pages | 7 |
| Journal | Operations Research |
| Volume | 63 |
| Issue number | 2 |
| DOIs | |
| State | Published - 1 Mar 2015 |
| Externally published | Yes |
Keywords
- Gradient estimation
- Monte Carlo simulation
- Quantile
- Sensitivity analysis
Fingerprint
Dive into the research topics of 'Technical note-on estimating quantile sensitivities via infinitesimal perturbation analysis'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver