A spectral surrogate model for stochastic simulators computed from trajectory samples

DOI10.1016/j.cma.2022.115875OpenAlexW4285428910WikidataQ128176512 ScholiaQ128176512MaRDI QIDQ2686878

Nora Lüthen, Bruno Sudret, Stefano Marelli

Publication date: 1 March 2023

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2207.05653

zbMATH Keywords

statistical inferencerandom fieldspolynomial chaos expansionKarhunen-Loève expansionsurrogate modelingstochastic simulators

Mathematics Subject Classification ID

Statistics (62-XX) Biology and other natural sciences (92-XX)

Uses Software

• fda (R)
• KernSmooth
• UQLab
• CopulaModel

Cites Work

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• Pair-copula constructions of multiple dependence
• Practical Heteroscedastic Gaussian Process Modeling for Large Simulation Experiments
• Numerical methods for the discretization of random fields by means of the Karhunen-Loève expansion
• Probabilistic models for stochastic elliptic partial differential equations
• Adaptive sparse polynomial chaos expansion based on least angle regression
• Global sensitivity analysis of stochastic computer models with joint metamodels
• An introduction to copulas.
• Stochastic model reduction for chaos representations
• Polynomial chaos representation of spatio-temporal random fields from experimental measurements
• Principal components analysis of sampled functions
• Design and analysis of computer experiments. With comments and a rejoinder by the authors
• Vines -- a new graphical model for dependent random variables.
• Smoothing methods in statistics
• Analyzing stochastic computer models: a review with opportunities
• Bayesian neural networks: an introduction and survey
• Data-driven polynomial chaos expansion for machine learning regression
• Spectral representation of stochastic field data using sparse polynomial chaos expansions
• Functional data analysis.
• Karhunen-Loève approximation of random fields by generalized fast multipole methods
• On the convergence of generalized polynomial chaos expansions
• A non-intrusive model reduction approach for polynomial chaos expansion using proper orthogonal decomposition
• Stochastic Kriging for Simulation Metamodeling
• Dependence Modeling with Copulas
• Maximum likelihood estimation of stochastic chaos representations from experimental data
• Approximation spline de l'analyse en composantes principales d'une variable aléatoire hilbertienne
• Simulation of Stationary Process Via a Sampling Theorem
• The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
• A Spline Chaos Expansion
• Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark
• SURROGATE MODELING OF STOCHASTIC FUNCTIONS-APPLICATION TO COMPUTATIONAL ELECTROMAGNETIC DOSIMETRY
• SENSITIVITY ANALYSIS FOR STOCHASTIC SIMULATORS USING DIFFERENTIAL ENTROPY
• REPLICATION-BASED EMULATION OF THE RESPONSE DISTRIBUTION OF STOCHASTIC SIMULATORS USING GENERALIZED LAMBDA DISTRIBUTIONS
• Automatic selection of basis-adaptive sparse polynomial chaos expansions for engineering applications
• Emulation of Stochastic Simulators Using Generalized Lambda Models
• Nonintrusive Polynomial Chaos Expansions for Sensitivity Analysis in Stochastic Differential Equations
• A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options
• Emulators for stochastic simulation codes
• A Class of Statistics with Asymptotically Normal Distribution
• Optimal Transport