<p>Modeling a response over a nonconvex design region is a common problem in diverse areas such as engineering and geophysics. The tools available to model and design for such responses are limited and have received little attention. We propose a new method for selecting design points over nonconvex regions that is based on the application of multidimensional scaling to the geodesic distance. Optimal designs for prediction are described, with special emphasis on Gaussian process models, followed by a simulation study and an application in glaciology. Supplementary materials for this article are available online.</p
International audienceAuthor(s): Victor Picheny, Postdoctorate Researcher Department of Applied Math...
Experimental designs for estimating the axial slopes of a response surface are considered. For the s...
The construction of models aimed at learning the behaviour of a system whose responses to inputs are...
Modeling a response over a non-convex design region is a common problem in diverse areas such as eng...
ii Modeling a response over a non-convex design region is a common problem in diverse areas such as ...
Computer models are used as surrogates for physical experiments in many areas of science. They can a...
A good experimental design in a non-parametric framework, such as Gaussian process modelling in comp...
Many researchers use computer simulators as experimental tools, especially when physical experiments...
Presented at the 9th Multi-Disciplinary Analysis and Optimization Symposium in Atlanta, GA, Septembe...
In order to efficiently optimize the problem involving complex computer codes or computationally exp...
Computer models are used as replacements for physical experiments in a wide variety of applications....
As computer experiments are widely used in engineering and various other fields of science and techn...
International audienceIn the context of expensive deterministic simulations, Gaussian process(GP) mo...
The main objective of the paper is to describe and develop model oriented methods and algorithms for...
Multidimensional scaling is very common in exploratory data analysis. It is mainly used to represent...
International audienceAuthor(s): Victor Picheny, Postdoctorate Researcher Department of Applied Math...
Experimental designs for estimating the axial slopes of a response surface are considered. For the s...
The construction of models aimed at learning the behaviour of a system whose responses to inputs are...
Modeling a response over a non-convex design region is a common problem in diverse areas such as eng...
ii Modeling a response over a non-convex design region is a common problem in diverse areas such as ...
Computer models are used as surrogates for physical experiments in many areas of science. They can a...
A good experimental design in a non-parametric framework, such as Gaussian process modelling in comp...
Many researchers use computer simulators as experimental tools, especially when physical experiments...
Presented at the 9th Multi-Disciplinary Analysis and Optimization Symposium in Atlanta, GA, Septembe...
In order to efficiently optimize the problem involving complex computer codes or computationally exp...
Computer models are used as replacements for physical experiments in a wide variety of applications....
As computer experiments are widely used in engineering and various other fields of science and techn...
International audienceIn the context of expensive deterministic simulations, Gaussian process(GP) mo...
The main objective of the paper is to describe and develop model oriented methods and algorithms for...
Multidimensional scaling is very common in exploratory data analysis. It is mainly used to represent...
International audienceAuthor(s): Victor Picheny, Postdoctorate Researcher Department of Applied Math...
Experimental designs for estimating the axial slopes of a response surface are considered. For the s...
The construction of models aimed at learning the behaviour of a system whose responses to inputs are...