Convex relaxation for IMSE optimal design in random-field models
From MaRDI portal
Publication:1658175
DOI10.1016/j.csda.2016.10.018zbMath1464.62078OpenAlexW2539544406MaRDI QIDQ1658175
Luc Pronzato, Bertrand Gauthier
Publication date: 14 August 2018
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2016.10.018
integral operatorrandom-field modeloptimal design of experimentsIMSEBayesian linear modelkernel reduction
Computational methods for problems pertaining to statistics (62-08) Random fields; image analysis (62M40) Optimal statistical designs (62K05)
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Cites Work
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- Optimal designs for Gaussian process models via spectral decomposition
- Optimal Bayesian experimental design for linear models
- Numerical estimation of a probability measure
- A vertex-exchange-method in D-optimal design theory
- Interpolation of spatial data. Some theory for kriging
- The design and analysis of computer experiments.
- Design and analysis of computer experiments. With comments and a rejoinder by the authors
- Design of experiments in nonlinear models. Asymptotic normality, optimality criteria and small-sample properties
- Spatial sampling design and covariance-robust minimax prediction based on convex design ideas
- A delimitation of the support of optimal designs for Kiefer's \(\phi _p\)-class of criteria
- Approximation of IMSE-optimal Designs via Quadrature Rules and Spectral Decomposition
- Spectral Approximation of the IMSE Criterion for Optimal Designs in Kernel-Based Interpolation Models
- Support Vector Machines
- Branch-and-Bound Search for Experimental Designs Based on D Optimality and Other Criteria
- The intrinsic random functions and their applications
- The Bayesian bridge between simple and universal Kriging