Maximum likelihood estimation for Gaussian processes under inequality constraints
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Publication:2323946
DOI10.1214/19-EJS1587zbMath1428.62420arXiv1804.03378OpenAlexW2972250097MaRDI QIDQ2323946
Andrés F. López-Lopera, François Bachoc, Agnès Lagnoux
Publication date: 13 September 2019
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1804.03378
asymptotic normalityGaussian processesinequality constraintsfixed-domain asymptoticsconstrained maximum likelihood
Asymptotic properties of parametric estimators (62F12) Inference from spatial processes (62M30) Gaussian processes (60G15)
Related Items (7)
Sequential Construction and Dimension Reduction of Gaussian Processes Under Inequality Constraints ⋮ Finite-dimensional approximation of Gaussian processes with linear inequality constraints and noisy observations ⋮ Maximum Likelihood Estimation and Uncertainty Quantification for Gaussian Process Approximation of Deterministic Functions ⋮ Short Communication: Beyond Surrogate Modeling: Learning the Local Volatility via Shape Constraints ⋮ Composite likelihood estimation for a Gaussian process under fixed domain asymptotics ⋮ Gaussian field on the symmetric group: prediction and learning ⋮ Asymptotic Analysis of Maximum Likelihood Estimation of Covariance Parameters for Gaussian Processes: An Introduction with Proofs
Uses Software
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