Generalization of the Kimeldorf-Wahba correspondence for constrained interpolation

DOI10.1214/16-EJS1149zbMath1348.60055arXiv1602.02714MaRDI QIDQ302441

Hassan Maatouk, Xavier Bay, Laurence Grammont

Publication date: 5 July 2016

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1602.02714

zbMATH Keywords

interpolationGaussian processBayes estimationinequality constraintsreproducing kernel Hilbert spacemaximum a posteriori estimatorKimeldorf-Wahba correspondence

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Gaussian processes (60G15) Bayesian inference (62F15) Hilbert spaces with reproducing kernels (= (proper) functional Hilbert spaces, including de Branges-Rovnyak and other structured spaces) (46E22) Prediction theory (aspects of stochastic processes) (60G25) Response surface designs (62K20)

Related Items (8)

Kriging of financial term-structures ⋮ Unnamed Item ⋮ Gaussian process emulators for computer experiments with inequality constraints ⋮ A new method for interpolating in a convex subset of a Hilbert space ⋮ Sequential Construction and Dimension Reduction of Gaussian Processes Under Inequality Constraints ⋮ Finite-dimensional approximation of Gaussian processes with linear inequality constraints and noisy observations ⋮ Approximating Gaussian Process Emulators with Linear Inequality Constraints and Noisy Observations via MC and MCMC ⋮ Finite-Dimensional Gaussian Approximation with Linear Inequality Constraints

Uses Software

• GAUSSIAN
• constrKriging

Cites Work

• Kriging of financial term-structures
• Smoothing noisy data under monotonicity constraints existence, characterization and convergence rates
• Gaussian process emulators for computer experiments with inequality constraints
• A new method for interpolating in a convex subset of a Hilbert space
• Smoothing and Interpolation in a Convex Subset of a Hilbert Space
• A Correspondence Between Bayesian Estimation on Stochastic Processes and Smoothing by Splines
• Theory of Reproducing Kernels

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