This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Random Variable Estimation and Model Calibration in the Presence of Epistemic and Aleatory Uncertainties

Journal Article
2018-01-1105
ISSN: 1946-3979, e-ISSN: 1946-3987
Published April 03, 2018 by SAE International in United States
Random Variable Estimation and Model Calibration in the Presence of Epistemic and Aleatory Uncertainties
Sector:
Citation: Gaymann, A., Pietropaoli, M., Crespo, L., Kenny, S. et al., "Random Variable Estimation and Model Calibration in the Presence of Epistemic and Aleatory Uncertainties," SAE Int. J. Mater. Manf. 11(4):453-466, 2018, https://doi.org/10.4271/2018-01-1105.
Language: English

References

  1. Glickman, M. Schroeder, B. and Romero, V. , “Cantilever Beam End-to-End UQ Test Problem: Handling Experimental and Simulation Uncertainties in Model Calibration, Model Validation, and Risk Assessment, Sandia National Laboratories,” SAND2017-4689 O, 2017.
  2. Helton, J.C., Oberkampf, W. et al. , “Challenge Problems: Uncertainty in System Response Given Uncertain Parameters,” Reliability Engineering and System Safety 85:11-19, 2004.
  3. Roy, C. and Oberkampf, W. , “A Comprehensive Framework for Verification, Validation, and Uncertainty Quantification in Scientific Computing,” Computer Methods in Applied Mechanics and Engineering 200(2011):2131-2144, 2004.
  4. Nakos, J.T. , “Uncertainty Analysis of Thermocouple Measurements Used in Normal and Abnormal Thermal Environment Experiments at Sandia Radiant Heat Facility and Lurance Canyon Burn Site,” Sandia National Labs., SAND2004-1023, Apr. 2004.
  5. Hosking, J.R.M. and Wallis, J.R. , “Guide to the Evaluation of Measurement Uncertainty for Quantitative Test Results,” EUROLAB, Paris, France, Aug. 2006, 8, Retrieved Mar. 2, 2017.
  6. Chakraborti, S. and Dickinson Gibbons, J. , Nonparametric Statistical Inference, Fifth Edition, STATISTICS: Textbooks and Monographs (Chapman and Hall/CRC Press, 2010), ISBN:9781420077612.
  7. Kraaikamp, C., Dekkling, F.M. et al. , A Modern Introduction to Probability and Statistics, Springer Texts in Statistics (2005).
  8. Wolfowitz, J., Dvoretzky, A., and Kiefer, J. , “Asymptotic Minimax Character of the Sample Distribution Function and of the Classical Multinomial Estimator,” The Annals of Mathematical Statistics 27(3):642-669, 1956.
  9. Massart, P. , “The Tight Constant in the Dvoretzky-Kiefer-Wolfowitz Inequality,” The Annals of Probability, 1990.
  10. Scholz, F.W. , “Nonparametric Tail Extrapolation,” Technical Report, ISSTECH-95-014, Boeing Information & Support Services, 1995.
  11. Donald, A.M. and Scarrott, C. , “Review of Extreme Value Threshold Estimation and Uncertainty Quantification,” Statistical Journal 10(1):33-60, 2012.
  12. Rutledge, J. and Warner, B.A. , “Simple Nonparametric Upper and Lower Tolerance Bounds Based on Order Statistics,” USAFA/DFMS, n.d.
  13. Learned-Miller, E. and DeStefano, J. , “A Probabilistic Upper Bound on Differential Entropy,” IEEE Transactions on Information Theory, 2008.
  14. Natarajan, K., Betrsimas, D. et al. , “Tight Bounds on Expected Order Statistics,” Probability in the Engineering and Information Sciences, 2006.
  15. Hosking, J.R.M. and Wallis, J.R. , “Parameter and Quantile Estimation for the Generalized Pareto Distribution,” Technometrics 29(3):339-349, 1987.
  16. Dufour, J.M. and Diouf, M.A. , “Improved Nonparametric Inference for the Mean of a Bounded Random Variable with Application to Poverty Measures,” Working Paper, Departement de Sciences Economiques, Universite de Montreal, May 2005.
  17. Lezaud, P. and Charras-Garrido, M. , “Extreme Value Analysis: An Introduction,” Journal de la Societe Francaise de Statistique, 2013.
  18. Tawn, J.A. and Papastathopoulos, I. , “Extended Generalized Pareto Models for Tail Estimation,” Journal of Statistical Planning and Inference 143:131-143, 2013.
  19. Anderson, T.W. , “Confidence Limits for the Value of an Arbitrary Bounded Random Variable with a Continuous Distribution Function,” Bulletin of the International and Statistical Institute, 1969.
  20. Wolf, M. and Romano, J.P. , “Explicit Nonparametric Confidence Intervals for the Variance with Guaranteed Coverage,” Communications in Statistics - Theory and Methods, 2002.
  21. Reynolds, D.A. , “Gaussian Mixture Models,” in: Encyclopedia of Biometrics (2009).
  22. Clifton, L., Clifton, D.A. et al. , “Extending the Generalized Pareto Distribution for Novelty Detection in High-Dimensional Spaces,” Journal of Signal Processing Systems 2014 74(3):323-339, Aug. 2013.

Cited By