메뉴 건너뛰기




Volumn 113, Issue 1, 2013, Pages 30-41

Analysis of computationally demanding models with continuous and categorical inputs

Author keywords

Categorical inputs; Emulator; Gaussian process; Meta model; Non parametric regression; Sensitivity analysis; Surrogate model; Uncertainty analysis

Indexed keywords

COMPUTATIONAL METHODS; COMPUTER SIMULATION; SENSITIVITY ANALYSIS; UNCERTAINTY ANALYSIS;

EID: 84872698560     PISSN: 09518320     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ress.2012.11.018     Document Type: Article
Times cited : (31)

References (61)
  • 3
    • 34548585030 scopus 로고    scopus 로고
    • Multiple predictor smoothing methods for sensitivity analysis: Description of techniques
    • DOI 10.1016/j.ress.2006.10.012, PII S0951832006002316
    • C.B. Storlie, and J.C. Helton Multiple predictor smoothing methods for sensitivity analysis description of techniques Reliability Engineering and System Safety 93 2008 28 54 (Pubitemid 47391224)
    • (2008) Reliability Engineering and System Safety , vol.93 , Issue.1 , pp. 28-54
    • Storlie, C.B.1    Helton, J.C.2
  • 4
    • 67949092696 scopus 로고    scopus 로고
    • Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models
    • C.B. Storlie, L.P. Swiler, J.C. Helton, and C.J. Sallaberry Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models Reliability Engineering and System Safety 94 2009 1735 1763
    • (2009) Reliability Engineering and System Safety , vol.94 , pp. 1735-1763
    • Storlie, C.B.1    Swiler, L.P.2    Helton, J.C.3    Sallaberry, C.J.4
  • 5
    • 33847764070 scopus 로고    scopus 로고
    • Functionally induced priors for the analysis of experiments
    • DOI 10.1198/004017006000000372
    • V.R. Joseph, and J.D. Delaney Functionally induced priors for the analysis of experiments Technometrics 49 2007 1 11 (Pubitemid 46373229)
    • (2007) Technometrics , vol.49 , Issue.1 , pp. 1-11
    • Joseph, V.R.1    Delaney, J.D.2
  • 6
    • 55149088117 scopus 로고    scopus 로고
    • Gaussian process models for computer experiments with qualitative and quantitative factors
    • P. Qian, H. Wu, and C.F.J. Wu Gaussian process models for computer experiments with qualitative and quantitative factors Technometrics 50 2008 383 396
    • (2008) Technometrics , vol.50 , pp. 383-396
    • Qian, P.1    Wu, H.2    Wu, C.F.J.3
  • 7
    • 54949111733 scopus 로고    scopus 로고
    • Bayesian treed Gaussian process models with an application to computer modeling
    • R.B. Gramacy, and H.K. Lee Bayesian treed Gaussian process models with an application to computer modeling Journal of the American Statistical Association 103 2008 1119 1130
    • (2008) Journal of the American Statistical Association , vol.103 , pp. 1119-1130
    • Gramacy, R.B.1    Lee, H.K.2
  • 11
    • 0001727377 scopus 로고    scopus 로고
    • Special issue: The 1996 performance assessment for the waste isolation pilot plant
    • Helton JC, Marietta MG, editors. Special issue: the 1996 performance assessment for the waste isolation pilot plant. Reliability Engineering and System Safety 2000;69:1-451.
    • (2000) Reliability Engineering and System Safety , vol.69 , pp. 1-451
    • Helton, J.C.1    Marietta, M.G.2
  • 15
    • 0023822856 scopus 로고
    • An investigation of uncertainty and sensitivity analysis techniques for computer models
    • R.L. Iman, and J.C. Helton An investigation of uncertainty and sensitivity analysis techniques for computer models Risk Analysis 8 1988 71 90
    • (1988) Risk Analysis , vol.8 , pp. 71-90
    • Iman, R.L.1    Helton, J.C.2
  • 16
    • 77951675271 scopus 로고    scopus 로고
    • Sandia National Laboratories US Department of Energy Office of Civilian Radioactive Waste Management, MDL-WIS-PA-000005 Rev 00, AD 01. Las Vegas, NV
    • Sandia National Laboratories. Total system performance assessment model/analysis for the license application. US Department of Energy Office of Civilian Radioactive Waste Management, MDL-WIS-PA-000005 Rev 00, AD 01. Las Vegas, NV, 2008.
    • (2008) Total System Performance Assessment Model/analysis for the License Application
  • 17
    • 84866312095 scopus 로고    scopus 로고
    • Uncertainty and sensitivity analysis in performance assessment for the proposed repository for high-level radioactive waste at Yucca Mountain, Nevada
    • Helton JC, Hansen CW, Sallaberry CJ. Uncertainty and sensitivity analysis in performance assessment for the proposed repository for high-level radioactive waste at Yucca Mountain, Nevada. Reliability Engineering and System Safety, 2012;107;44-63.
    • (2012) Reliability Engineering and System Safety , vol.107 , pp. 44-63
    • Helton, J.C.1    Hansen, C.W.2    Sallaberry, C.J.3
  • 18
    • 78650732213 scopus 로고    scopus 로고
    • Surface estimation, variable selection, and the nonparametric oracle property
    • C.B. Storlie, H.D. Bondell, B.J. Reich, and H.H. Zhang Surface estimation, variable selection, and the nonparametric oracle property Statistica Sinica 21 2010 679 705
    • (2010) Statistica Sinica , vol.21 , pp. 679-705
    • Storlie, C.B.1    Bondell, H.D.2    Reich, B.J.3    Zhang, H.H.4
  • 19
    • 65349194393 scopus 로고    scopus 로고
    • Variable selection in Bayesian smoothing spline ANOVA models application to deterministic computer codes
    • B.J. Reich, C.B. Storlie, and H.D. Bondell Variable selection in Bayesian smoothing spline ANOVA models application to deterministic computer codes Technometrics 51 2009 110 120
    • (2009) Technometrics , vol.51 , pp. 110-120
    • Reich, B.J.1    Storlie, C.B.2    Bondell, H.D.3
  • 22
    • 67749122116 scopus 로고    scopus 로고
    • Prediction for computer experiments having quantitative and qualitative input variables
    • G. Han, T.J. Santner, and W.I. Notz Prediction for computer experiments having quantitative and qualitative input variables Technometrics 51 3 2009 278 288
    • (2009) Technometrics , vol.51 , Issue.3 , pp. 278-288
    • Han, G.1    Santner, T.J.2    Notz, W.I.3
  • 23
    • 84865486245 scopus 로고
    • Principles of geostatistics
    • G. Matheron Principles of geostatistics Economic Geology 58 1963 1246 1266
    • (1963) Economic Geology , vol.58 , pp. 1246-1266
    • Matheron, G.1
  • 26
    • 33845260356 scopus 로고    scopus 로고
    • Variable selection for Gaussian process models in computer experiments
    • DOI 10.1198/004017006000000228
    • C. Linkletter, D. Bingham, N. Hengartner, D. Higdon, and K. Ye Variable selection for Gaussian process models in computer experiments Technometrics 48 2006 478 490 (Pubitemid 44865389)
    • (2006) Technometrics , vol.48 , Issue.4 , pp. 478-490
    • Linkletter, C.1    Bingham, D.2    Hengartner, N.3    Higdon, D.4    Ye, K.Q.5
  • 31
    • 0002432565 scopus 로고
    • Multivariate adaptive regression splines (with discussion)
    • J.H. Friedman Multivariate adaptive regression splines (with discussion) Annals of Statistics 19 1991 1 141
    • (1991) Annals of Statistics , vol.19 , pp. 1-141
    • Friedman, J.H.1
  • 34
    • 34250263445 scopus 로고
    • Smoothing noisy data with spline functions estimating the correct degree of smoothing by the method of generalized cross-validation
    • P. Craven, and G. Wahba Smoothing noisy data with spline functions estimating the correct degree of smoothing by the method of generalized cross-validation Numerical Mathematics 31 1979 377 403
    • (1979) Numerical Mathematics , vol.31 , pp. 377-403
    • Craven, P.1    Wahba, G.2
  • 42
    • 33847350805 scopus 로고    scopus 로고
    • Component selection and smoothing in smoothing spline analysis of variance models
    • Y. Lin, and H. Zhang Component selection and smoothing in smoothing spline analysis of variance models Annals of Statistics 34 2006 2272 2297
    • (2006) Annals of Statistics , vol.34 , pp. 2272-2297
    • Lin, Y.1    Zhang, H.2
  • 46
    • 4043135554 scopus 로고    scopus 로고
    • Optimal predictive model selection
    • DOI 10.1214/009053604000000238
    • M. Barbieri, and J. Berger Optimal predictive model selection Annals of Statistics 32 2004 870 897 (Pubitemid 41250287)
    • (2004) Annals of Statistics , vol.32 , Issue.3 , pp. 870-897
    • Barbieri, M.M.1    Berger, J.O.2
  • 48
    • 0030532505 scopus 로고    scopus 로고
    • Bayesian variable selection and related predictors
    • H. Chipman Bayesian variable selection and related predictors Canadian Journal of Statistics 24 1996 17 36
    • (1996) Canadian Journal of Statistics , vol.24 , pp. 17-36
    • Chipman, H.1
  • 49
    • 0031526204 scopus 로고    scopus 로고
    • Approaches for bayesian variable selection
    • E.I. George, and R.E. McCulloch Approaches for Bayesian variable selection Statistica Sinica 7 1997 339 373 (Pubitemid 127473668)
    • (1997) Statistica Sinica , vol.7 , Issue.2 , pp. 339-373
    • George, E.I.1    McCulloch, R.E.2
  • 50
    • 0033079533 scopus 로고    scopus 로고
    • A quantitative model-independent method for global sensitivity analysis of model output
    • A. Saltelli, S. Tarantola, and K. Chan A quantitative model-independent method for global sensitivity analysis of model output Technometrics 41 1999 39 56
    • (1999) Technometrics , vol.41 , pp. 39-56
    • Saltelli, A.1    Tarantola, S.2    Chan, K.3
  • 52
    • 0002807631 scopus 로고    scopus 로고
    • Hitchhiker's guide to sensitivity analysis
    • A. Saltelli, K. Chan, M. Scott, John Wiley & Sons New York, NY
    • F. Campolongo, A. Saltelli, T. Sorensen, and S. Tarantola Hitchhiker's guide to sensitivity analysis A. Saltelli, K. Chan, M. Scott, Sensitivity analysis 2000 John Wiley & Sons New York, NY 15 47
    • (2000) Sensitivity Analysis , pp. 15-47
    • Campolongo, F.1    Saltelli, A.2    Sorensen, T.3    Tarantola, S.4
  • 53
    • 0036080354 scopus 로고    scopus 로고
    • Illustration of sampling-based methods for uncertainty and sensitivity analysis
    • DOI 10.1111/0272-4332.00041
    • J.C. Helton, and F.J. Davis Illustration of sampling-based methods for uncertainty and sensitivity analysis Risk Analysis 22 2002 591 622 (Pubitemid 34657259)
    • (2002) Risk Analysis , vol.22 , Issue.3 , pp. 591-622
    • Helton, J.C.1    Davis, F.J.2
  • 54
    • 34548576866 scopus 로고    scopus 로고
    • Multiple predictor smoothing methods for sensitivity analysis: Example results
    • DOI 10.1016/j.ress.2006.10.013, PII S0951832006002328
    • C.B. Storlie, and J.C. Helton Multiple predictor smoothing methods for sensitivity analysis example results Reliability Engineering and System Safety 93 2008 55 77 (Pubitemid 47391225)
    • (2008) Reliability Engineering and System Safety , vol.93 , Issue.1 , pp. 55-77
    • Storlie, C.B.1    Helton, J.C.2
  • 55
    • 0343454039 scopus 로고    scopus 로고
    • Representation of two-phase flow in the vicinity of the repository in the 1996 performance assessment for the waste isolation pilot plant
    • P. Vaughn, J.E. Bean, J.C. Helton, M.E. Lord, R.J. MacKinnon, and J.D. Schreiber Representation of two-phase flow in the vicinity of the repository in the 1996 performance assessment for the waste isolation pilot plant Reliability Engineering and System Safety 69 2000 205 226
    • (2000) Reliability Engineering and System Safety , vol.69 , pp. 205-226
    • Vaughn, P.1    Bean, J.E.2    Helton, J.C.3    Lord, M.E.4    MacKinnon, R.J.5    Schreiber, J.D.6
  • 56
    • 0041399511 scopus 로고    scopus 로고
    • Bayesian inference for the uncertainty distribution of computer model outputs
    • DOI 10.1093/biomet/89.4.769
    • J.E. Oakley, and A. O'Hagan Bayesian inference for the uncertainty distribution of computer model outputs Biometrika 89 2002 769 784 (Pubitemid 41311943)
    • (2002) Biometrika , vol.89 , Issue.4 , pp. 769-784
    • Oakley, J.1    O'Hagan, A.2
  • 57
    • 0018468345 scopus 로고
    • Comparison of three methods for selecting values of input variables in the analysis of output from a computer code
    • M.D. McKay, R.J. Beckman, and W.J. Conover A comparison of three methods for selecting values of input variables in the analysis of output from a computer code Technometrics 21 1979 239 245 (Pubitemid 9452235)
    • (1979) Technometrics , vol.21 , Issue.2 , pp. 239-245
    • McKay, M.D.1    Beckman, R.J.2    Conover, W.J.3
  • 58
    • 0038476492 scopus 로고    scopus 로고
    • Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems
    • J.C. Helton, and F.J. Davis Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems Reliability Engineering and System Safety 81 2003 23 69
    • (2003) Reliability Engineering and System Safety , vol.81 , pp. 23-69
    • Helton, J.C.1    Davis, F.J.2
  • 59
    • 0037363336 scopus 로고    scopus 로고
    • A distribution-free test for the relationship between model input and output when using Latin hypercube sampling
    • S.C. Hora, and J.C. Helton A distribution-free test for the relationship between model input and output when using Latin hypercube sampling Reliability Engineering and System Safety 79 1996 333 339
    • (1996) Reliability Engineering and System Safety , vol.79 , pp. 333-339
    • Hora, S.C.1    Helton, J.C.2
  • 60
    • 0000439277 scopus 로고    scopus 로고
    • Non-stationary spatial modeling
    • J.M. Bernardo, J.O. Berger, A.P. Dawid, A.F.M. Smith, Oxford University Press Oxford, UK
    • D. Higdon, J. Swall, and J. Kern Non-stationary spatial modeling J.M. Bernardo, J.O. Berger, A.P. Dawid, A.F.M. Smith, Bayesian Statistics vol. 6 1999 Oxford University Press Oxford, UK 761 768
    • (1999) Bayesian Statistics , vol.6 VOL. , pp. 761-768
    • Higdon, D.1    Swall, J.2    Kern, J.3
  • 61
    • 0042401905 scopus 로고    scopus 로고
    • Spectral methods for nonstationary spatial processes
    • DOI 10.1093/biomet/89.1.197
    • M. Fuentes Spectral methods for nonstationary spatial processes Biometrika 89 2002 197 210 (Pubitemid 41312011)
    • (2002) Biometrika , vol.89 , Issue.1 , pp. 197-210
    • Fuentes, M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.