Input Distribution Selection for Simulation Experiments: Accounting for Input Uncertainty
Published Online:1 Oct 2001https://doi.org/10.1287/opre.49.5.744.10606
References
- Discrete-Event System Simulation (1996) 2nd ed.(Prentice-Hall, Inc., Upper Saddle River, NJ, USA) Google Scholar
- Intuitive estimation of means. Psychonomic Science (1966) 5:161–162Crossref, Google Scholar
- Statistical Decision Theory and Bayesian Analysis (1985) 2nd ed.(Springer-Verlag, New York) Crossref, Google Scholar
- The intrinsic Bayes factor for model selection and prediction. J. of the Amer. Statist. Association (1996) 91(433):109–122Crossref, Google Scholar
- Bayesian Theory (1994) (Wiley, Chichester, UK) Crossref, Google Scholar
- Bayesian model choice via Markov chain Monte Carlo. J. of the Royal Statist. Soc., Ser. B (1995) 57:473–484Google Scholar
- Bayes and Empirical Bayes Methods for Data Analysis (1996) (Chapman & Hall, London) Google Scholar
- , Tew J. D., Manivannan S., Sadowski D. A., Seila A. F. Selecting input models. Proceedings of the Winter Simulation Conference (1994) (Institute of Electrical and Electronics Engineers, Inc., Piscataway, NJ) 184–191Crossref, Google Scholar
- Estimating parameters in continuous univariate distributions with a shifted origin. J. Royal Statist. Soc., Series B (1983) 45:394–403Google Scholar
- Sensitivity of computer simulation experiments to errors in input data. J. on Statist. Comput. and Simulation (1997) 57:219–241Crossref, Google Scholar
- The use of maximum likelihood estimates in X2 tests for goodness of fit. Ann. of Math. Statist. (1954) 25:579–586Crossref, Google Scholar
- Uncertainty in dispersion and deposition accident consequence modelling assessed with performance-based expert judgement. Reliability Engrg. and System Safety (1994) 45:35–46Crossref, Google Scholar
- Theory of Probability v. 2 (1990) (John Wiley & Sons Inc., New York) Google Scholar
- Visual interactive fitting of bounded Johnson distributions. SIMULATION (1989) 52:199–205Crossref, Google Scholar
- Computing Bayes factors by combining simulation and asymptotic approximations. (1995) . Technical Report TR-630, Statistics Department, Carnegie Mellon UniversityGoogle Scholar
- Assessment and propogation of model uncertainty (with discussion). J. of the Royal Statist. Soc. Series B. (1995) 57(1):45–97Google Scholar
- Methods for approximating integrals in statistics with special emphasis on Bayesian integration problems. Statist. Sci. (1995) 10(3):254–272Crossref, Google Scholar
- , Gilks W. R., Richardson S., Spiegelhalter D. J. Model determination using sampling-based methods. Markov Chain Monte Carlo in Practice (1996) (Chapman and Hall, London)Crossref, Google Scholar
- , Gilks W. R., Richardson S., Spiegelhalter D. J. Stochastic search variable selection. Markov Chain Monte Carlo in Practice (1996) (Chapman and Hall, London)Google Scholar
- Adaptive rejection metropolis sampling. Appl. Statist. (1995) 44:455–472Crossref, Google Scholar
- Markov Chain Monte Carlo in Practice (1996) (Chapman and Hall, London)Crossref, Google Scholar
- Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika (1995) 82:711–732Crossref, Google Scholar
- Treatment of uncertainty in performance assessments for complex systems. Risk Anal. (1994) 14:483–511Crossref, Google Scholar
- The three-parameter lognormal distribution and Bayesian analysis of a point-source epidemic. J. of the Amer. Statist. Association (1963) 58:72–84Crossref, Google Scholar
- Sensitivity of a Bayesian analysis to the prior distribution. IEEE Trans. Syst. Man Cybernet (1994) 24(2):216–221Crossref, Google Scholar
- Judgment under Uncertainty: Heuristics and Biases (1982) (Cambridge University Press, Cambridge) Crossref, Google Scholar
- Bayes factors. J. of the Amer. Statist. Association (1995) 90(430):773–795Crossref, Google Scholar
- Some diagnostics of maximum likelihood and posterior nonnormality. The Ann. of Statist. (1994) 22(2):668–695Crossref, Google Scholar
- A reference Bayesian test for nested hypotheses and its relationship to the Schwarz criterion. J. of the Amer. Statist. Association (1995) 90(431):928–934Crossref, Google Scholar
- The selection of prior distributions by formal rules. J. of the Amer. Statist. Association (1996) 91(435):1343–1370Crossref, Google Scholar
- Perceived variability. J. of Experimental Psychology (1967) 73:498–502Crossref, Google Scholar
- Simulation Modeling & Analysis (1991) 2nd ed.(McGraw-Hill, Inc., New York) Google Scholar
- , Alexopoulos C., Kang K., Lilegdon W. R., Goldsman D. Input modeling for discrete-event simulation. Proceedings of the Winter Simulation Conference (1995) (Institute of Electrical and Electronics Engineers, Inc., Piscataway, NJ) 16–23Crossref, Google Scholar
- Model selection and accounting for model uncertainty in graphical models using Occam's window. J. of the Amer. Statist. Association (1994) 89:1535–1546Crossref, Google Scholar
- Bayesian graphical models for discrete data. Internat. Statist. Rev. (1995) 63(2):215–232Crossref, Google Scholar
- Exact sampling from a continuous state space. Scandinavian J. of Statist. (1998) 25:483–502Crossref, Google Scholar
- Fractional Bayes factors for model comparison (with discussion). J. of the Royal Statist. Soc. Series B (1995) 56:99–118Google Scholar
- Properities of intrinsic and fractional bayes factors. Test (1997) 6:101–118Crossref, Google Scholar
- , Marsden P. V. Bayesian model selection in social research (with discussion by Andrew Gelman & Donald B. Rubin and Robert M. Hauser, and a rejoinder). Sociological Methodology 1995 (1995) (Blackwells, Cambridge, MS)Google Scholar
- , Gilks W. R., Richardson S., Spiegelhalter D. J. Hypothesis testing and model selection. Markov Chain Monte Carlo in Practice (1996) (Champman and Hall, London)Google Scholar
- Bayesian model averaging for linear regression models. J. of the Amer. Statist. Association (1997) 92(437):179–191Crossref, Google Scholar
- On Bayesian analysis of mixtures with an unknown number of components. J. of the Royal Statist. Soc. B (1997) 59(4):731–792Crossref, Google Scholar
- The Foundations of Statistics (1972) (Dover Publications Inc., New York) Google Scholar
- , Charnes J. M., Morrice D. J., Brunner D. T., Swain J. J. Uncertainty and sensitivity studies of models of environmental systems. Proceedings of the Winter Simulation Conference (1996) (Institute of Electrical and Electronics Engineers, Inc., Piscataway, NJ) 255–259Crossref, Google Scholar
- A further study of estimating averages. Ergonomics (1963) 6:255–265Crossref, Google Scholar
- , Gilks W. R., Richardson S., Spiegelhalter D. J. Hepatitis B: a case study in MCMC methods. Markov Chain Monte Carlo in Practice (1996) (chapman and Hall, London)Crossref, Google Scholar
- Markov chains for exploring posterior distributions. The Ann. of Statist. (1994) 22(4):1701–1762Crossref, Google Scholar
- Bayesian model averaging in proportional hazard models: Assessing stroke risk. (1996) . Technical Report no. 302, University of Washington, Department of Statistics, Seattle, WAGoogle Scholar
- Graphical interactive simulation input modeling with bivariate Bézier distributions. ACM Trans. on Modeling and Comput. Simulation (1995) 5(3):163–189Crossref, Google Scholar
- , Tew J. D., Manivannan S., Sadowski D. A., Seila A. F. Downtime data—its collection analysis, and importance. Proceedings of the Winter Simulation Conference (1994) (Institute of Electrical and Electronics Engineers, Inc., Piscataway, NJ) 1040–1043Crossref, Google Scholar

