On degeneracy and invariances of random fields paths with applications in Gaussian process modelling

DOI10.1016/j.jspi.2015.10.002zbMath1329.60135OpenAlexW2195861446MaRDI QIDQ899361

David Ginsbourger, Nicolas Durrande, Olivier Roustant

Publication date: 28 December 2015

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://boris.unibe.ch/73011/8/On%20degeneracy%20and%20invariances%20of%20random%20fields%20paths%20with%20applications%20in%20Gaussian%20process%20modelling%20%282%29.pdf

zbMATH Keywords

random fieldslinear operatorsGaussian process modelingcovariance kernelsstructural priors

Mathematics Subject Classification ID

Random fields (60G60) Gaussian processes (60G15) Probabilistic models, generic numerical methods in probability and statistics (65C20) General nonlinear regression (62J02) Sample path properties (60G17)

Related Items (5)

Warped Gaussian Processes and Derivative-Based Sequential Designs for Functions with Heterogeneous Variations ⋮ Quantifying uncertainty on Pareto fronts with Gaussian process conditional simulations ⋮ Covariance models and Gaussian process regression for the wave equation. Application to related inverse problems ⋮ Gaussian process optimization with failures: classification and convergence proof ⋮ A supermartingale approach to Gaussian process based sequential design of experiments

Uses Software

• hgam
• kergp
• DiceDesign

Cites Work

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