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Computer Model Calibration Using High-Dimensional Output

Citations

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Cited by:

  1. Leatherman, Erin R. & Dean, Angela M. & Santner, Thomas J., 2017. "Designing combined physical and computer experiments to maximize prediction accuracy," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 346-362.
  2. Giri Gopalan & Christopher K. Wikle, 2022. "A Higher-Order Singular Value Decomposition Tensor Emulator for Spatiotemporal Simulators," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(1), pages 22-45, March.
  3. Perrin, G., 2020. "Adaptive calibration of a computer code with time-series output," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
  4. Huaimin Diao & Yan Wang & Dianpeng Wang, 2022. "A D-Optimal Sequential Calibration Design for Computer Models," Mathematics, MDPI, vol. 10(9), pages 1-15, April.
  5. Zhang, Yang & Xu, Jun & Gardoni, Paolo, 2024. "A loading contribution degree analysis-based strategy for time-variant reliability analysis of structures under multiple loading stochastic processes," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
  6. Ioannis Andrianakis & Ian R Vernon & Nicky McCreesh & Trevelyan J McKinley & Jeremy E Oakley & Rebecca N Nsubuga & Michael Goldstein & Richard G White, 2015. "Bayesian History Matching of Complex Infectious Disease Models Using Emulation: A Tutorial and a Case Study on HIV in Uganda," PLOS Computational Biology, Public Library of Science, vol. 11(1), pages 1-18, January.
  7. Daniel W. Gladish & Ross Darnell & Peter J. Thorburn & Bhakti Haldankar, 2019. "Emulated Multivariate Global Sensitivity Analysis for Complex Computer Models Applied to Agricultural Simulators," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(1), pages 130-153, March.
  8. Wu, Xu & Kozlowski, Tomasz & Meidani, Hadi, 2018. "Kriging-based inverse uncertainty quantification of nuclear fuel performance code BISON fission gas release model using time series measurement data," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 422-436.
  9. Paulo, Rui & García-Donato, Gonzalo & Palomo, Jesús, 2012. "Calibration of computer models with multivariate output," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 3959-3974.
  10. Kleijnen, Jack P.C. & Mehdad, E., 2014. "Multivariate Versus Univariate Kriging Metamodels for Multi-Response Simulation Models (Revision of 2012-039)," Discussion Paper 2014-012, Tilburg University, Center for Economic Research.
  11. Kleijnen, Jack P.C. & Mehdad, E., 2012. "Kriging in Multi-response Simulation, including a Monte Carlo Laboratory (Replaced by 2014-012)," Other publications TiSEM cf311469-5f8c-4c1e-ad4f-6, Tilburg University, School of Economics and Management.
  12. Jung, Yongsu & Lee, Ikjin, 2021. "Optimal design of experiments for optimization-based model calibration using Fisher information matrix," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
  13. Matthew Plumlee, 2014. "Fast Prediction of Deterministic Functions Using Sparse Grid Experimental Designs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1581-1591, December.
  14. Hwang, Youngdeok & Kim, Hang J. & Chang, Won & Yeo, Kyongmin & Kim, Yongku, 2019. "Bayesian pollution source identification via an inverse physics model," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 76-92.
  15. Guillaume Perrin & Christian Soize, 2020. "Adaptive method for indirect identification of the statistical properties of random fields in a Bayesian framework," Computational Statistics, Springer, vol. 35(1), pages 111-133, March.
  16. Kim, Wongon & Yoon, Heonjun & Lee, Guesuk & Kim, Taejin & Youn, Byeng D., 2020. "A new calibration metric that considers statistical correlation: Marginal Probability and Correlation Residuals," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
  17. Bruno Sansó & Chris Forest, 2009. "Statistical calibration of climate system properties," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(4), pages 485-503, September.
  18. Chen, Yewen & Chang, Xiaohui & Luo, Fangzhi & Huang, Hui, 2023. "Additive dynamic models for correcting numerical model outputs," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
  19. K. Sham Bhat & David S. Mebane & Priyadarshi Mahapatra & Curtis B. Storlie, 2017. "Upscaling Uncertainty with Dynamic Discrepancy for a Multi-Scale Carbon Capture System," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1453-1467, October.
  20. McClarren, Ryan G. & Ryu, D. & Paul Drake, R. & Grosskopf, Michael & Bingham, Derek & Chou, Chuan-Chih & Fryxell, Bruce & van der Holst, Bart & Paul Holloway, James & Kuranz, Carolyn C. & Mallick, Ban, 2011. "A physics informed emulator for laser-driven radiating shock simulations," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 1194-1207.
  21. Sophie Marque-Pucheu & Guillaume Perrin & Josselin Garnier, 2020. "An efficient dimension reduction for the Gaussian process emulation of two nested codes with functional outputs," Computational Statistics, Springer, vol. 35(3), pages 1059-1099, September.
  22. Giannakeas, Ilias N. & Mazaheri, Fatemeh & Bacarreza, Omar & Khodaei, Zahra Sharif & Aliabadi, Ferri M.H., 2023. "Probabilistic residual strength assessment of smart composite aircraft panels using guided waves," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
  23. Liu, Yushan & Li, Luyi & Zhao, Sihan & Song, Shufang, 2021. "A global surrogate model technique based on principal component analysis and Kriging for uncertainty propagation of dynamic systems," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
  24. Jackson Samuel E. & Vernon Ian & Liu Junli & Lindsey Keith, 2020. "Understanding hormonal crosstalk in Arabidopsis root development via emulation and history matching," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 19(2), pages 1-33, April.
  25. SungKu Kang & Ran Jin & Xinwei Deng & Ron S. Kenett, 2023. "Challenges of modeling and analysis in cybermanufacturing: a review from a machine learning and computation perspective," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 415-428, February.
  26. Samantha M. Roth & Ben Seiyon Lee & Sanjib Sharma & Iman Hosseini‐Shakib & Klaus Keller & Murali Haran, 2023. "Flood hazard model calibration using multiresolution model output," Environmetrics, John Wiley & Sons, Ltd., vol. 34(2), March.
  27. Wilkinson Richard David, 2013. "Approximate Bayesian computation (ABC) gives exact results under the assumption of model error," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 12(2), pages 129-141, May.
  28. Laura Cartwright & Andrew Zammit‐Mangion & Nicholas M. Deutscher, 2023. "Emulation of greenhouse‐gas sensitivities using variational autoencoders," Environmetrics, John Wiley & Sons, Ltd., vol. 34(2), March.
  29. Manfren, Massimiliano & Aste, Niccolò & Moshksar, Reza, 2013. "Calibration and uncertainty analysis for computer models – A meta-model based approach for integrated building energy simulation," Applied Energy, Elsevier, vol. 103(C), pages 627-641.
  30. White, Staci A. & Herbei, Radu, 2015. "A Monte Carlo approach to quantifying model error in Bayesian parameter estimation," Computational Statistics & Data Analysis, Elsevier, vol. 83(C), pages 168-181.
  31. Mevin Hooten & Christopher Wikle & Michael Schwob, 2020. "Statistical Implementations of Agent‐Based Demographic Models," International Statistical Review, International Statistical Institute, vol. 88(2), pages 441-461, August.
  32. Matthew F. Dixon & Nicholas G. Polson & Kemen Goicoechea, 2022. "Deep Partial Least Squares for Empirical Asset Pricing," Papers 2206.10014, arXiv.org.
  33. Jung, Yongsu & Jo, Hwisang & Choo, Jeonghwan & Lee, Ikjin, 2022. "Statistical model calibration and design optimization under aleatory and epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
  34. Antony M. Overstall & David C. Woods, 2013. "A Strategy for Bayesian Inference for Computationally Expensive Models with Application to the Estimation of Stem Cell Properties," Biometrics, The International Biometric Society, vol. 69(2), pages 458-468, June.
  35. Pulong Ma & Georgios Karagiannis & Bledar A. Konomi & Taylor G. Asher & Gabriel R. Toro & Andrew T. Cox, 2022. "Multifidelity computer model emulation with high‐dimensional output: An application to storm surge," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(4), pages 861-883, August.
  36. Geoffrey Fairchild & Kyle S. Hickmann & Susan M. Mniszewski & Sara Y. Del Valle & James M. Hyman, 2014. "Optimizing human activity patterns using global sensitivity analysis," Computational and Mathematical Organization Theory, Springer, vol. 20(4), pages 394-416, December.
  37. Giri Gopalan & Birgir Hrafnkelsson & Christopher K. Wikle & Håvard Rue & Guðfinna Aðalgeirsdóttir & Alexander H. Jarosch & Finnur Pálsson, 2019. "A Hierarchical Spatiotemporal Statistical Model Motivated by Glaciology," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(4), pages 669-692, December.
  38. Daniel W. Gladish & Daniel E. Pagendam & Luk J. M. Peeters & Petra M. Kuhnert & Jai Vaze, 2018. "Emulation Engines: Choice and Quantification of Uncertainty for Complex Hydrological Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(1), pages 39-62, March.
  39. Stripling, H.F. & Adams, M.L. & McClarren, R.G. & Mallick, B.K., 2011. "The Method of Manufactured Universes for validating uncertainty quantification methods," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 1242-1256.
  40. Bledar A. Konomi & Georgios Karagiannis & Kevin Lai & Guang Lin, 2017. "Bayesian Treed Calibration: An Application to Carbon Capture With AX Sorbent," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 37-53, January.
  41. Sudipto Banerjee, 2023. "Discussion of “Saving Storage in Climate Ensembles: A Model-Based Stochastic Approach” by Huang Huang, Stefano Castruccio, Allison H. Baker and Marc Genton," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(2), pages 365-369, June.
  42. Matthew Plumlee & V. Roshan Joseph & Hui Yang, 2016. "Calibrating Functional Parameters in the Ion Channel Models of Cardiac Cells," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 500-509, April.
  43. Mohammadi, Hossein & Challenor, Peter & Goodfellow, Marc, 2019. "Emulating dynamic non-linear simulators using Gaussian processes," Computational Statistics & Data Analysis, Elsevier, vol. 139(C), pages 178-196.
  44. Nott, David J. & Marshall, Lucy & Fielding, Mark & Liong, Shie-Yui, 2014. "Mixtures of experts for understanding model discrepancy in dynamic computer models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 491-505.
  45. Maupin, Kathryn A. & Swiler, Laura P., 2020. "Model discrepancy calibration across experimental settings," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
  46. Grant Hutchings & Bruno Sansó & James Gattiker & Devin Francom & Donatella Pasqualini, 2023. "Comparing emulation methods for a high‐resolution storm surge model," Environmetrics, John Wiley & Sons, Ltd., vol. 34(3), May.
  47. Kleijnen, Jack P.C. & Mehdad, Ehsan, 2014. "Multivariate versus univariate Kriging metamodels for multi-response simulation models," European Journal of Operational Research, Elsevier, vol. 236(2), pages 573-582.
  48. Williams, Brian J. & Loeppky, Jason L. & Moore, Leslie M. & Macklem, Mason S., 2011. "Batch sequential design to achieve predictive maturity with calibrated computer models," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 1208-1219.
  49. Jeremy Rohmer, 2014. "Dynamic sensitivity analysis of long-running landslide models through basis set expansion and meta-modelling," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 73(1), pages 5-22, August.
  50. Hemez, François M. & Atamturktur, Sezer, 2011. "The dangers of sparse sampling for the quantification of margin and uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 1220-1231.
  51. Drignei, Dorin, 2011. "A general statistical model for computer experiments with time series output," Reliability Engineering and System Safety, Elsevier, vol. 96(4), pages 460-467.
  52. Luca Aiello & Matteo Fontana & Alessandra Guglielmi, 2023. "Bayesian functional emulation of CO2 emissions on future climate change scenarios," Environmetrics, John Wiley & Sons, Ltd., vol. 34(8), December.
  53. Curtis B. Storlie & William A. Lane & Emily M. Ryan & James R. Gattiker & David M. Higdon, 2015. "Calibration of Computational Models With Categorical Parameters and Correlated Outputs via Bayesian Smoothing Spline ANOVA," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 68-82, March.
  54. Kim, Wongon & Lee, Guesuk & Son, Hyejeong & Choi, Hyunhee & Youn, Byeng D., 2022. "Estimation of fatigue crack initiation and growth in engineering product development using a digital twin approach," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
  55. Won Chang & Murali Haran & Patrick Applegate & David Pollard, 2016. "Calibrating an Ice Sheet Model Using High-Dimensional Binary Spatial Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(513), pages 57-72, March.
  56. Qin, Zhiyuan & Naser, M.Z., 2023. "Machine learning and model driven bayesian uncertainty quantification in suspended nonstructural systems," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
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