Multiple predictor smoothing methods for sensitivity analysis: Description of techniques

Reliability Engineering and System Safety

Volumn 93, Issue 1, 2008, Pages 28-54

  Storlie, Curtis B ^a   Helton, Jon C ^b  

^a NORTH CAROLINA STATE UNIVERSITY   (United States)

^b ARIZONA STATE UNIVERSITY   (United States)

Author keywords

Additive models; Epistemic uncertainty; Locally weighted regression; Nonparametric regression; Projection pursuit regression; Recursive partitioning regression; Scatterplot smoothing; Sensitivity analysis; Stepwise selection; Uncertainty analysis

Indexed keywords

MATHEMATICAL MODELS; NONLINEAR ANALYSIS; RECURSIVE FUNCTIONS; REGRESSION ANALYSIS; SENSITIVITY ANALYSIS; UNCERTAINTY ANALYSIS;

ADDITIVE MODELS; EPISTEMIC UNCERTAINTY; LOCALLY WEIGHTED REGRESSION; NONPARAMETRIC REGRESSION; PROJECTION PURSUIT REGRESSION; RECURSIVE PARTITIONING REGRESSION; SCATTERPLOT SMOOTHING; STEPWISE SELECTION;

COMPUTATIONAL METHODS;

EID: 34548585030     PISSN: 09518320     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ress.2006.10.012     Document Type: Article

References (143)

1. Christie M.A., Glimm J., Grove J.W., Higdon D.M., Sharp D.H., and Wood-Schultz M.M. Error analysis and simulations of complex phenomena. Los Alamos Sci 29 (2005) 6-25
2. Sharp D.H., and Wood-Schultz M.M. QMU and nuclear weapons certification: what's under the hood?. Los Alamos Sci 28 (2003) 47-53
3. Wagner R.L. Science, uncertainty and risk: the problem of complex phenomena. APS News 12 1 (2003) 8
4. Oberkampf W.L., DeLand S.M., Rutherford B.M., Diegert K.V., and Alvin K.F. Error and uncertainty in modeling and simulation. Reliab Eng Syst Saf 75 3 (2002) 333-357
5. Risk Assessment Forum. Guiding principles for Monte Carlo analysis, EPA/630/R-97/001 (1997), US Environmental Protection Agency, Washington DC (available from the NTIS as PB97-188106/XAB)
6. NCRP (National Council on Radiation Protection and Measurements). A guide for uncertainty analysis in dose and risk assessments related to environmental contamination, NCRP commentary no. 14. Bethesda, MD: National Council on Radiation Protection and Measurements, 1996.
7. NRC (National Research Council). Science and judgment in risk assessment (1994), National Academy Press, Washington, DC
8. NRC (National Research Council). Issues in risk assessment (1993), National Academy Press, Washington, DC
9. US EPA (US Environmental Protection Agency). An SAB report: multi-media risk assessment for radon, review of uncertainty analysis of risks associated with exposure to radon, EPA-SAB-RAC-93-014 (1993), US Environmental Protection Agency, Washington, DC
10. IAEA (International Atomic Energy Agency). Evaluating the reliability of predictions made using environmental transfer models, Safety series no. 100 (1989), International Atomic Energy Agency, Vienna
11. Beck M.B. Water-quality modeling: a review of the analysis of uncertainty. Water Resour Res 23 8 (1987) 1393-1442
12. Cacuci D.G. Sensitivity and uncertainty analysis, vol. 1: theory (2003), Chapman & Hall/CRC Press, Boca Raton, FL
13. Turányi T. Sensitivity analysis of complex kinetic systems. Tools and applications. J Math Chem 5 3 (1990) 203-248
14. Rabitz H., Kramer M., and Dacol D. Sensitivity analysis in chemical kinetics. In: Rabinovitch B.S., Schurr J.M., and Strauss H.L. (Eds). Annual review of physical chemistry vol. 34 (1983), Annual Reviews Inc., Palo Alto, CA 419-461
15. In: Lewins J., and Becker M. (Eds). Sensitivity and uncertainty analysis of reactor performance parameters vol. 14 (1982), Plenum Press, New York, NY
16. Frank P.M. Introduction to system sensitivity theory (1978), Academic Press, New York, NY
17. Tomovic R., and Vukobratovic M. General sensitivity theory (1972), Elsevier, New York, NY
18. Myers R.H., Montgomery D.C., Vining G.G., Borror C.M., and Kowalski S.M. Response surface methodology: a retrospective and literature review. J Quality Technol 36 1 (2004) 53-77
19. Myers R.H. Response surface methodology-current status and future directions. J Quality Technol 31 1 (1999) 30-44
20. Andres T.H. Sampling methods and sensitivity analysis for large parameter sets. J Statist Comput Simul 57 1-4 (1997) 77-110
21. Kleijnen J.P.C. Sensitivity analysis and related analyses: a review of some statistical techniques. J Statist Comput Simul 57 1-4 (1997) 111-142
22. Kleijnen J.P.C. Sensitivity analysis of simulation experiments: regression analysis and statistical design. Math Comput Simul 34 3-4 (1992) 297-315
23. Sacks J., Welch W.J., Mitchel T.J., and Wynn H.P. Design and analysis of computer experiments. Statist Sci 4 4 (1989) 409-435
24. Morton R.H. Response surface methodology. Math Scient 8 (1983) 31-52
25. Mead R., and Pike D.J. A review of response surface methodology from a biometric viewpoint. Biometrics 31 (1975) 803-851
26. Myers R.H. Response surface methodology (1971), Allyn and Bacon, Boston, MA
27. Helton J.C., and Davis F.J. Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems. Reliab Eng Sys Saf 81 1 (2003) 23-69
28. Helton J.C., and Davis F.J. Illustration of sampling-based methods for uncertainty and sensitivity analysis. Risk Anal 22 3 (2002) 591-622
29. Helton J.C., and Davis F.J. Sampling-based methods. In: Saltelli A., Chan K., and Scott E.M. (Eds). Sensitivity analysis (2000), Wiley, New York, NY 101-153
30. Kleijnen J.P.C., and Helton J.C. Statistical analyses of scatterplots to identify important factors in large-scale simulations, 1: Review and comparison of techniques. Reliab Eng Syst Saf 65 2 (1999) 147-185
31. Blower S.M., and Dowlatabadi H. Sensitivity and uncertainty analysis of complex models of disease transmission: an HIV model, as an example. Int Statist Rev 62 2 (1994) 229-243
32. Saltelli A., Andres T.H., and Homma T. Sensitivity analysis of model output. An investigation of new techniques. Comput Statist Data Anal 15 2 (1993) 445-460
33. Iman R.L. Uncertainty and sensitivity analysis for computer modeling applications. In: Cruse T.A. (Ed). Reliability technology-1992, The winter annual meeting of the American Society of Mechanical Engineers, Anaheim, California, November 8-13, 1992 vol. 28 (1992), American Society of Mechanical Engineers, Aerospace Division, New York, NY 153-168
34. Saltelli A., and Marivoet J. Non-parametric statistics in sensitivity analysis for model output. A comparison of selected techniques. Reliab Eng Syst Saf 28 2 (1990) 229-253
35. Iman R.L., Helton J.C., and Campbell J.E. An approach to sensitivity analysis of computer models, Part 1. Introduction, input variable selection and preliminary variable assessment. J Quality Technol 13 3 (1981) 174-183
36. Iman R.L., Helton J.C., and Campbell J.E. An approach to sensitivity analysis of computer models, Part 2. Ranking of input variables, response surface validation, distribution effect and technique synopsis. J Qual Technol 13 4 (1981) 232-240
37. Iman R.L., and Conover W.J. Small sample sensitivity analysis techniques for computer models, with an application to risk assessment. Commun Statist Theory Meth A9 17 (1980) 1749-1842
38. McKay M.D., Beckman R.J., and Conover W.J. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 21 2 (1979) 239-245
39. Li G., Rosenthal C., and Rabitz H. High-dimensional model representations. J Phys Chem 105 33 (2001) 7765-7777
40. Rabitz H., and Alis O.F. General foundations of high-dimensional model representations. J Math Chem 25 2-3 (1999) 197-233
41. Saltelli A., Tarantola S., and Chan K.P.-S. A quantitative model-independent method for global sensitivity analysis of model output. Technometrics 41 1 (1999) 39-56
42. Sobol' I.M. Sensitivity estimates for nonlinear mathematical models. Math Model Comput Exp 1 4 (1993) 407-414
43. Cukier R.I., Levine H.B., and Shuler K.E. Nonlinear Sensitivity analysis of multiparameter model systems. J Comput Phys 26 1 (1978) 1-42
44. Saltelli A., Ratto M., Tarantola S., and Campolongo F. Sensitivity analysis for chemical models. Chem Rev 105 7 (2005) 2811-2828
45. Ionescu-Bujor M., and Cacuci D.G. A comparative review of sensitivity and uncertainty analysis of large-scale systems-I: deterministic methods. Nucl Sci Eng 147 3 (2004) 189-2003
46. Cacuci D.G., and Ionescu-Bujor M. A comparative review of sensitivity and uncertainty analysis of large-scale systems-II: statistical methods. Nucl Sci Eng 147 3 (2004) 204-217
47. Frey H.C., and Patil S.R. Identification and review of sensitivity analysis methods. Risk Anal 22 3 (2002) 553-578
48. In: Saltelli A., Chan K., and Scott E.M. (Eds). Sensitivity analysis (2000), Wiley, New York, NY
49. Hamby D.M. A review of techniques for parameter sensitivity analysis of environmental models. Environ Monit Assess 32 2 (1994) 135-154
50. Helton J.C. Uncertainty and sensitivity analysis techniques for use in performance assessment for radioactive waste disposal. Reliab Eng Syst Saf 42 2-3 (1993) 327-367
51. Ronen Y. Uncertainty analysis (1988), CRC Press, Inc., Boca Raton, FL
52. Iman R.L., and Helton J.C. An investigation of uncertainty and sensitivity analysis techniques for computer models. Risk Anal 8 1 (1988) 71-90
53. Vaughn P., Bean J.E., Helton J.C., Lord M.E., MacKinnon R.J., and Schreiber J.D. Representation of two-phase flow in the vicinity of the repository in the 1996 performance assessment for the Waste Isolation Pilot Plant. Reliab Eng Sys Saf 69 1-3 (2000) 205-226
54. Helton J.C., and Breeding R.J. Calculation of reactor accident safety goals. Reliab Eng Sys Saf 39 2 (1993) 129-158
55. Breeding R.J., Helton J.C., Gorham E.D., and Harper F.T. Summary description of the methods used in the probabilistic risk assessments for NUREG-1150. Nucl Eng Des 135 1 (1992) 1-27
56. Helton J.C., and Marietta M.G. Special issue: the 1996 performance assessment for the Waste Isolation Pilot Plant. Reliab Eng Sys Saf 69 1-3 (2000) 1-451
57. Helton J.C., Anderson D.R., Jow H.-N., Marietta M.G., and Basabilvazo G. Performance assessment in support of the 1996 compliance certification application for the Waste Isolation Pilot Plant. Risk Anal 19 5 (1999) 959-986
58. Garthwaite P.H., Kadane J.B., and O'Hagan A. Statistical methods for eliciting probability distributions. J Am Statist Assoc 100 470 (2005) 680-700
59. Cooke R.M., and Goossens L.H.J. Expert judgement elicitation for risk assessment of critical infrastructures. J Risk Res 7 6 (2004) 643-656
60. Ayyub B.M. Elicitation of expert opinions for uncertainty and risks (2001), CRC Press, Boca Raton, FL
61. McKay M., and Meyer M. Critique of and limitations on the use of expert judgements in accident consequence uncertainty analysis. Radiat Protect Dosim 90 3 (2000) 325-330
62. Goossens L.H.J., Harper F.T., Kraan B.C.P., and Metivier H. Expert judgement for a probabilistic accident consequence uncertainty analysis. Radiat Protect Dosim 90 3 (2000) 295-301
63. Budnitz R.J., Apostolakis G., Boore D.M., Cluff L.S., Coppersmith K.J., Cornell C.A., et al. Use of technical expert panels: applications to probabilistic seismic hazard analysis. Risk Anal 18 4 (1998) 463-469
64. Goossens L.H.J., and Harper F.T. Joint EC/USNRC Expert judgement driven radiological protection uncertainty analysis. J Radiol Protect 18 4 (1998) 249-264
65. Siu N.O., and Kelly D.L. Bayesian parameter estimation in probabilistic risk assessment. Reliab Eng Syst Saf 62 1-2 (1998) 89-116
66. Evans J.S., Gray G.M., Sielken Jr. G.L., Smith A.E., Valdez-Flores C., and Graham J.D. Use of probabilistic expert judgement in uncertainty analysis of carcinogenic potency. Regul Toxicol Pharmacol 20 1 pt.1 (1994) 15-36
67. Thorne M.C. The use of expert opinion in formulating conceptual models of underground disposal systems and the treatment of associated bias. Reliab Eng Syst Saf 42 2-3 (1993) 161-180
68. Chhibber S., Apostolakis G., and Okrent D. A taxonomy of issues related to the use of expert judgments in probabilistic safety studies. Reliab Eng Syst Saf 38 1-2 (1992) 27-45
69. Otway H., and Winterfeldt D.V. Expert judgement in risk analysis and management: process, context, and pitfalls. Risk Anal 12 1 (1992) 83-93
70. Thorne M.C., and Williams M.M.R. A review of expert judgement techniques with reference to nuclear safety. Progr Nucl Saf 27 2-3 (1992) 83-254
71. Cooke R.M. Experts in uncertainty: opinion and subjective probability in science (1991), Oxford University Press, Oxford, New York
72. Meyer M.A., and Booker J.M. Eliciting and analyzing expert judgment: a practical guide (1991), Academic Press, New York, NY
73. Hora S.C., and Iman R.L. Expert opinion in risk analysis: the NUREG-1150 methodology. Nucl Sci Eng 102 4 (1989) 323-331
74. Helton J.C. Uncertainty and sensitivity analysis in the presence of stochastic and subjective uncertainty. J Statist Comput Simul 57 1-4 (1997) 3-76
75. Helton J.C., and Burmaster D.E. Guest editorial: treatment of aleatory and epistemic uncertainty in performance assessments for complex systems. Reliab Eng Syst Saf 54 2-3 (1996) 91-94
76. Paté-Cornell M.E. Uncertainties in risk analysis: six levels of treatment. Reliab Eng Syst Saf 54 2-3 (1996) 95-111
77. Winkler R.L. Uncertainty in probabilistic risk assessment. Reliab Eng Syst Saf 54 2-3 (1996) 127-132
78. Hoffman F.O., and Hammonds J.S. Propagation of uncertainty in risk assessments: the need to distinguish between uncertainty due to lack of knowledge and uncertainty due to variability. Risk Anal 14 5 (1994) 707-712
79. Helton J.C. Treatment of uncertainty in performance assessments for complex systems. Risk Anal 14 4 (1994) 483-511
80. Apostolakis G. The concept of probability in safety assessments of technological systems. Science 250 4986 (1990) 1359-1364
81. Haan C.T. Parametric uncertainty in hydrologic modeling. Trans ASAE 32 1 (1989) 137-146
82. Parry G.W., and Winter P.W. Characterization and evaluation of uncertainty in probabilistic risk analysis. Nucl Saf 22 1 (1981) 28-42
83. Kaplan S., and Garrick B.J. On the quantitative definition of risk. Risk Analy 1 1 (1981) 11-27
84. Kleijnen J.P.C., and Helton J.C. Statistical analyses of scatterplots to identify important factors in large-scale simulations, 2: robustness of techniques. Reliab Eng Syst Saf 65 2 (1999) 187-197
85. Assunçao R. Testing spatial randomness by means of angles. Biometrics 50 (1994) 531-537
86. Ripley B.D. Spatial point pattern analysis in ecology. In: Legendre P., and Legendre L. (Eds). Developments in numerical ecology. NATO ASI series, series G: ecological sciences vol. 14 (1987), Springer, Berlin, New York 407-430
87. Zeng G., and Dubes R.C. A comparison of tests for randomness. Pattern Recogn 18 2 (1985) 191-198
88. Diggle P.J., and Cox T.F. Some distance-based tests of independence for sparsely-sampled multivariate spatial point patterns. Int Statist Rev 51 1 (1983) 11-23
89. Byth K. On robust distance-based intensity estimators. Biometrics 38 1 (1982) 127-135
90. Byth K., and Ripley B.D. On sampling spatial patterns by distance methods. Biometrics 36 2 (1980) 279-284
91. Ripley B.D. Tests of randomness for spatial point patterns. J Roy Statist Soc 41 3 (1979) 368-374
92. Diggle P.J. Statistical methods for spatial point patterns in ecology. In: Cormack R.M., Ord J.K., and Fairfield M.D. (Eds). Spatial and temporal analysis in ecology (1979), International Co-operative Pub. House 95-150
93. Diggle P.J. On parameter estimation and goodness-of-fit testing for spatial point patterns. Biometrics 35 1 (1979) 87-101
94. Besag J., and Diggle P.J. Simple monte carlo tests for spatial pattern. Appl Statist 26 3 (1977) 327-333
95. Diggle P.J., Besag J., and Gleaves J.T. Statistical analysis of spatial point patterns by means of distance methods. Biometrics 32 (1976) 659-667
96. Cox T.F., and Lewis T. A conditioned distance ratio method for analyzing spatial patterns. Biometrika 63 3 (1976) 483-491
97. Holgate P. The use of distance methods for the analysis of spatial distribution of points. In: Lewis P.A.W. (Ed). Stochastic point processes: statistical analysis, theory, and applications (1972), Wiley-Interscience, New York, NY 122-135
98. Holgate P. Tests of randomness based on distance methods. Biometrika 52 3-4 (1965) 345-353
99. Garvey J.E., Marschall E.A., and Wright R.A. From star charts to stoneflies: detecting relationships in continuous bivariate data. Ecology 79 2 (1998) 442-447
100. Fasano G., and Franceschini A. A multidimensional version of the Kolmogorov-Smirnov test. Mont Not Roy Astronom Soc 225 1 (1987) 155-170
101. Gosset E. A 3-dimensional extended Kolmogorov-Smirnov test as a useful tool in astronomy. Astronom Astrophys 188 1 (1987) 258-264
102. Peacock J.A. Two-dimensional goodness-of-fit testing in astronomy. Mont Not Roy Astronom Soc 202 2 (1983) 615-627
103. Helton J.C., Davis F.J., and Johnson J.D. A comparison of uncertainty and sensitivity analysis results obtained with random and Latin hypercube sampling. Reliab Eng Syst Saf 89 3 (2005) 305-330
104. Hora S.C., and Helton J.C. A distribution-free test for the relationship between model input and output when using Latin hypercube sampling. Reliab Eng Syst Saf 79 3 (2003) 333-339
105. Mokhtari A., Frey H.C., and Jaykus L.A. Application of classification and regression trees for sensitivity analysis of the Escherichia coli O157: H7 food safety process risk model. J Food Protect 69 3 (2006) 609-618
106. Mishra S., Deeds N.E., and RamaRao B.S. Application of classification trees in the sensitivity analysis of probabilistic model results. Reliab Eng Syst Saf 79 2 (2003) 123-129
107. Storlie C.B., and Helton J.C. Multiple predictor smoothing methods for sensitivity analysis: example results. Reliab Eng Syst Saf 93 1 (2008) 55-77
108. Maindonald J., and Braun J. Data analysis and graphics using R (2003), Cambridge University Press, Cambridge
109. Insightful Corporation. S-PLUS 6 for windows guide to statistics Vol. 1 (2001), Insightful Corporation, Seattle, WA
110. Myers R.H. Classical and modern regression with applications. second ed (1990), Duxbury Press, Boston
111. Draper N.R., and Smith H. Applied regression analysis. second ed (1981), Wiley, New York, NY
112. Daniel C., Wood F.S., and Gorman J.W. Fitting equations to data: computer analysis of multifactor data. second ed (1980), Wiley, New York, NY
113. Seber G.A. Linear regression analysis (1977), Wiley, New York, NY
114. Neter J., and Wasserman W. Applied linear statistical models: regression, analysis of variance, and experimental designs (1974), Richard D. Irwin, Homewood, IL
115. Iman R.L., and Conover W.J. The use of the rank transform in regression. Technometrics 21 4 (1979) 499-509
116. Helton J.C. Uncertainty and sensitivity analysis in performance assessment for the Waste Isolation Pilot Plant. Comput Phys Commun 117 1-2 (1999) 156-180
117. Helton J.C., Johnson J.D., McKay M.D., Shiver A.W., and Sprung J.L. Robustness of an uncertainty and sensitivity analysis of early exposure results with the MACCS reactor accident consequence model. Reliab Eng Syst Saf 48 2 (1995) 129-148
118. Iman R.L., and Helton J.C. The repeatability of uncertainty and sensitivity analyses for complex probabilistic risk assessments. Risk Anal 11 4 (1991) 591-606
119. Myers R.H., and Montgomery D.C. Response surface methodology: process and product optimization using designed experiments (1995), Wiley, New York, NY
120. Huet S., Bouvier A., Gruet M.-A., and Jolivet E. Statistical tools for nonlinear regression: a practical guide with S-PLUS and R examples (2003), Springer, New York, NY
121. Hastie T.J., and Tibshirani R.J. Generalized additive models (1990), Chapman & Hall, London
122. Simonoff J.S. Smoothing methods in statistics (1996), Springer, New York, NY
123. Bowman A.W., and Azzalini A. Applied smoothing techniques for data analysis (1997), Clarendon, Oxford
124. Ruppert D., Ward M.P., and Carroll R.J. Semiparametric regression (2003), Cambridge University Press, Cambridge
125. Cleveland W.S. Robust locally weighted regression and smoothing scatterplots. J Am Statist Assoc 14 368 (1979) 829-836
126. Schimek M.G. Smoothing and regression: approaches, computation, and application (2000), Wiley, New York, NY
127. Chambers J.M., and Hastie T.J. Statistical models in S (1992), Wadsworth & Brooks, Pacific Grove, CA
128. Hocking R.R. Methods and applications of linear models (1996), Wiley, New York, NY
129. Christensen R. Plane answers to complex questions (1996), Springer, New York, NY
130. Allen D.M. The prediction sum of squares as a criterion for selecting predictor variables, 23 (1971), University of Kentucky, Department of Statistics, Lexington, KY
131. Friedman J.H., and Stuetzle W. Projection pursuit regression. J Am Statist Assoc 76 376 (1981) 817-823
132. Breiman L., Friedman J.H., Olshen R.A., and Stone C.J. Classification and regression trees (1984), Wadsworth Intl, Belmont, CA
133. Rousseeuw P.J., and Leroy A.M. Robust regression and outlier detection (1987), Wiley, New York, NY
134. Hastie T., Tibshirani R., and Friedman J. The elements of statistical learning: data mining, inference, and prediction (2001), Springer, New York, NY
135. Press W.H., Teukolsky S.A., Vetterlings W.T., and Flannery B.P. Numerical recipes: the art of scientific computing (FORTRAN Version). second ed (1992), Cambridge University Press, Cambridge
136. Hogg R.V., and Craig A.T. Introduction to mathematical statistics. fourth ed (1978), Macmillan, New York, NY
137. Breeding R.J., Helton J.C., Murfin W.B., Smith L.N., Johnson J.D., Jow H.-N., et al. The NUREG-1150 probabilistic risk assessment for the Surry Nuclear Power Station. Nucl Eng Des 135 1 (1992) 29-59
138. Payne Jr. A.C., Breeding R.J., Helton J.C., Smith L.N., Johnson J.D., Jow H.-N., et al. The NUREG-1150 probabilistic risk assessment for the Peach Bottom Atomic Power Station. Nucl Eng Des 135 1 (1992) 61-94
139. Gregory J.J., Breeding R.J., Helton J.C., Murfin W.B., Higgins S.J., and Shiver A.W. The NUREG-1150 probabilistic risk assessment for the Sequoyah Nuclear Plant. Nucl Eng Des 135 1 (1992) 92-115
140. Brown T.D., Breeding R.J., Helton J.C., Jow H.-N., Higgins S.J., and Shiver A.W. The NUREG-1150 probabilistic risk assessment for the Grand Gulf Nuclear Station. Nucl Eng Des 135 1 (1992) 117-137
141. Helton J.C., Martell M.-A., and Tierney M.S. Characterization of subjective uncertainty in the 1996 performance assessment for the Waste Isolation Pilot Plant. Reliab Eng Syst Saf 69 1-3 (2000) 191-204
142. CRWMS M&O (Civilian Radioactive Waste Management System Management and Operating Contractor). Total system performance assessment for the site recommendation, TDR-WIS-PA-000001 REV 00 (2000), CRWMS M&O, Las Vegas, NV
143. CRWMS M&O (Civilian Radioactive Waste Management System Management and Operating Contractor). Total system performance assessment (TSPA) model for site recommendation, MDL-WIS-PA-000002 REV 00 (2000), CRWMS M&O, Las Vegas, NV