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- Title
Kernel Estimation of Quantile Sensitivities.
- Authors
Liu, Guangwu; Hong, Liu Jeff
- Abstract
The article focuses on a study of the quantile sensitivities estimation with the use of stochastic simulation. It notes that quantile sensitivities are very useful in managing risk because it offers information on how output quantiles are affected by the changes in input parameters. It cites that a kernel estimator was proposed to prove its consistency and asymptotically normally distributed for outputs from both steady-state and terminating simulations.
- Subjects
SENSITIVITY analysis; RISK management in business; KERNEL functions; SIMULATION methods &; models; STOCHASTIC approximation
- Publication
Naval Research Logistics, 2009, Vol 56, Issue 6, p511
- ISSN
0894-069X
- Publication type
Article
- DOI
10.1002/nav.20358