Building metamodels for quantile-based measures using sectioning

Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013

Volumn , Issue , 2013, Pages 521-532

  Chen, Xi ^a   Kim, Kyoung Kuk ^b  

^a VIRGINIA COMMONWEALTH UNIVERSITY   (United States)

^b Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84894158330     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WSC.2013.6721447     Document Type: Conference Paper

References (23)

1. Acerbi, C., and D. Tasche. 2002. "On the coherence of expected shortfall". Journal of Banking & Fi- nance 26:1487-1503.
2. Alexopoulos, C., D. Goldsman, and J. R.Wilson. 2012. "A new perspective on batched quantile estimation". In Proceedings of the 2012 Winter Simulation Conference, edited by C. Laroque, J. Himmelspach, R. Pasupathy, O. Rose, and A. M. Uhrmacher. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc.
3. Ankenman, B. E., B. L. Nelson, and J. Staum. 2010. "Stochastic kriging for simulation metamodeling". Operations Research 58:371-382.
4. Asmussen, S., and P. W. Glynn. 2007. Stochastic Simulation. New York: Springer.
5. Avramidis, A. N., and J. R. Wilson. 1998. "Correlation-induction techniques for estimating quantiles in simulation experiments". Operations Research 46:574-591.
6. Baseball Prospectus 2013. "PECOTApercentiles are here". available at http://www.baseballprospectus.com/.
7. Chen, E. J., and W. D. Kelton. 1999. "Simulation-based estimation of quantiles". In Proceedings of the 1999 Winter Simulation Conference, edited by P. A. Farrington, U. B. Nembhard, D. T. Sturrock, and G. W. Evans, 428-434. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc.
8. Chen, X., B. E. Ankenman, and B. L. Nelson. 2012. "The effects of common random numbers on stochastic kriging metamodels". ACM Transactions on Modeling and Computer Simulation 22:7/1-7/20.
9. Chen, X., and K. Kim. 2013. "Stochastic kriging with biased sample estimates". Working Paper.
10. Chen, X., K. Kim, and B. L. Nelson. 2012. "Stochastic kriging for conditional value-at-risk and its sensitivi- Ties". In Proceedings of the 2012 Winter Simulation Conference, edited by C. Laroque, J. Himmelspach, R. Pasupathy, O. Rose, and A. M. Uhrmacher. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc.
11. Chu, F., and M. K. Nakayama. 2012. "Confidence intervals for quantiles when applying variance-reduction techniques". ACM Transactions on Modeling and Computer Simulation 22:10/1-10/25.
12. Efron, B. 1982. The Jackknife, the Bootstrap and Other Resampling Plans. Philadelphia: SIAM.
13. Efron, B., and C. Stein. 1981. "The jackknife estimate of variance". The Annals of Statistics 9:586-596.
14. Gordy, M. B., and S. Juneja. 2010. "Nested simulation in portfolio risk measurement". Management Science 56:1833-1848.
15. Hong, L. J., and G. Liu. 2009. "Simulation sensitivities of conditional value at risk". Management Science 55:281-293.
16. Hsu, J. C., and B. L. Nelson. 1990. "Control variates for quantile estimation". Management Science 36:835- 851.
17. JP Morgan, and Reuters. 1996. "RiskMetricsTM - Technical document". Fourth Edition, New York.
18. Liu, M., and J. Staum. 2010. "Stochastic kriging for efficient nested simulation of expected shortfall". Journal of Risk 12:3-27.
19. Nakayama, M. K. 2012. "Using sectioning to construct confidence intervals for quantiles when applying importance sampling". In Proceedings of the 2012 Winter Simulation Conference, edited by C. Laroque, J. Himmelspach, R. Pasupathy, O. Rose, and A. M. Uhrmacher. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc.
20. Parr, W. C., and W. R. Schucany. 1982. "Jackknifing L-statistics with smooth weight functions". Journal of the Americal Statistical Association 77:629-638.
21. Seila, A. F. 1982. "A batching approach to quantile estimation in regenerative simulations". Management Science 28:573-581.
22. Shao, J., and D. S. Tu. 1995. The Jackknife and Bootstrap. New York: Springer-Verlag.
23. Shao, J., and C. F. J. Wu. 1989. "A general theory for jackknife variance estimation". The Annals of Statistics 17:1176-1197.