Inverse Problem for a Time-Series Valued Computer Simulator via Scalarization

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"Inverse Problem for a Time-Series Valued Computer Simulator via Scalarization"
written by Pritam Ranjan, Mark Thomas, Holger Teismann, Sujay Mukhoti,
published by Open Journal of Statistics, Vol.6 No.3, 2016

has been cited by the following article(s):

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CrossRef

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	Journal of Statistical Theory and Practice, 2023

[2]	A Bayesian Approach to the Estimation of Parameters and Their Interdependencies in Environmental Modeling
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[3]	Solving an Inverse Problem for Time Series Valued Computer Simulators via Multiple Contour Estimation
	arXiv preprint arXiv:2211.01119, 2022

[4]	Targeted Adaptive Design
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[5]	Surrogate-enhanced parameter inference for function-valued models
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[6]	Inverse Problem for Dynamic Computer Simulators via Multiple Scalar-valued Contour Estimation
	2020

[7]	Statistical Modelling and Calibration of a Dynamic Computer Simulator
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[8]	Statistical Modelling and Analysis of the Computer-Simulated Datasets
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[9]	Statistical inverse identification for nonlinear train dynamics using a surrogate model in a Bayesian framework
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[10]	A history matching approach for calibrating hydrological models
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[11]	A sequential design approach for calibrating dynamic computer simulators
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[12]	Adaptive calibration of a computer code with time-series output
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[13]	A statistical approach for calibrating hydrologic models
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[14]	Statistical inverse problem in nonlinear high-speed train dynamics
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[15]	Local gaussian process model for large-scale dynamic computer experiments
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[16]	A Sequential Design Approach for Calibrating a Dynamic Population Growth Model
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[17]	Modeling and Analysis of Dynamic Computer Experiments
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[18]	Inverse Mapping for Rainfall-Runoff Models using History Matching Approach
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[1]	Targeted Adaptive Design SIAM/ASA Journal on Uncertainty Quantification, 2024 DOI:10.1137/22M149898X

[2]	Solving an Inverse Problem for Time-Series-Valued Computer Simulators via Multiple Contour Estimation Journal of Statistical Theory and Practice, 2023 DOI:10.1007/s42519-022-00312-5

[3]	Solving an Inverse Problem for Time-Series-Valued Computer Simulators via Multiple Contour Estimation Journal of Statistical Theory and Practice, 2023 DOI:10.1007/s42519-022-00312-5

[4]	A Bayesian Approach to the Estimation of Parameters and Their Interdependencies in Environmental Modeling Entropy, 2022 DOI:10.3390/e24020231

[5]	A Bayesian Approach to the Estimation of Parameters and Their Interdependencies in Environmental Modeling Entropy, 2022 DOI:10.3390/e24020231

[6]	Surrogate-Enhanced Parameter Inference for Function-Valued Models The 40th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, 2021 DOI:10.3390/psf2021003011

[7]	Surrogate-Enhanced Parameter Inference for Function-Valued Models The 40th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, 2021 DOI:10.3390/psf2021003011

[8]	Adaptive calibration of a computer code with time-series output Reliability Engineering & System Safety, 2020 DOI:10.1016/j.ress.2019.106728

[9]	A history matching approach for calibrating hydrological models Environmental and Ecological Statistics, 2019 DOI:10.1007/s10651-019-00420-9

[10]	Handbook of Research on Cloud Computing and Big Data Applications in IoT Advances in Computer and Electrical Engineering, 2019 DOI:10.4018/978-1-5225-8407-0.ch011

[11]	Statistical inverse identification for nonlinear train dynamics using a surrogate model in a Bayesian framework Journal of Sound and Vibration, 2019 DOI:10.1016/j.jsv.2019.06.024

[12]	A Sequential Design Approach for Calibrating Dynamic Computer Simulators SIAM/ASA Journal on Uncertainty Quantification, 2019 DOI:10.1137/18M1224544

[13]	Local Gaussian Process Model for Large-scale Dynamic Computer Experiments Journal of Computational and Graphical Statistics, 2018 DOI:10.1080/10618600.2018.1473778

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