PARAMETER AND UNCERTAINTY ESTIMATION FOR DYNAMICAL SYSTEMS USING SURROGATE STOCHASTIC PROCESSES.

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第一作者： Matthias,Chung

第一单位： Department of Mathematics, Computational Modeling and Data Analytics Division, Academy of Integrated Science, Virginia Tech, Blacksburg, VA 24061.

作者： Matthias,Chung ^[1] ; Mickaël,Binois ^[2] ; Robert B,Gramacy ^[3] ; Johnathan M,Bardsley ^[4] ; David J,Moquin ^[5] ; Amanda P,Smith ^[6] ; Amber M,Smith ^[6]

作者单位： Department of Mathematics, Computational Modeling and Data Analytics Division, Academy of Integrated Science, Virginia Tech, Blacksburg, VA 24061. ^[1] Booth School of Business, University of Chicago, Chicago, IL 60637. ^[2] Department of Statistics, Virginia Tech, Blacksburg, VA 24061. ^[3] Department of Mathematical Sciences, University of Montana, Missoula, MT 59812. ^[4] Department of Internal Medicine, University of Tennessee Health Science Center, Memphis, TN 38103. ^[5] Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN 38103. ^[6]

关键词 60G15 62F10 62F15 65L05 65L09 92-08 Gaussian process dynamical systems inverse problems parameter estimation uncertainty estimation viral kinetic model

DOI 10.1137/18M1213403

PMID 31749599

发布时间 2020-10-01

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