The main objective of the paper is to describe and develop model oriented methods and algorithms for the design of spatial experiments. Unlike many other publications in this area, the approach proposed here is essentially based on the ideas of convex design theory
International audienceThis work is devoted to the development of a new and efficient procedure for t...
When inference regards a finite spatial pattern, a model-based framework is commonly used, even if t...
Many applications in sensor networks require the estimation of spatial environmental fields. We focu...
Modeling a response over a non-convex design region is a common problem in diverse areas such as eng...
As computer experiments are widely used in engineering and various other fields of science and techn...
We study optimal sample designs for prediction with estimated parameters. Recent advances in the inf...
Spatial inference is usually carried out by means of model-based techniques, which estimate the unde...
13 pages, 1 article*Exploratory Model Selection for Spatially Designed Experiments--Some Examples* (...
This dissertation consists of three papers written on the design and analysis of experiments in the ...
We consider robust methods for the construction of sampling designs in spatial studies. The designs ...
A standard objective in computer experiments is to approximate the behaviour of an unknown function ...
The methods of optimal design of experiments are considered for the regression problem when the obse...
Resolvable row–column designs are widely used in field trials to control variation and improve the p...
AbstractWhen inference regards a finite spatial pattern, a model-based framework is commonly used, e...
A practical problem in spatial statistics is that of constructing spatial sampling designs for envir...
International audienceThis work is devoted to the development of a new and efficient procedure for t...
When inference regards a finite spatial pattern, a model-based framework is commonly used, even if t...
Many applications in sensor networks require the estimation of spatial environmental fields. We focu...
Modeling a response over a non-convex design region is a common problem in diverse areas such as eng...
As computer experiments are widely used in engineering and various other fields of science and techn...
We study optimal sample designs for prediction with estimated parameters. Recent advances in the inf...
Spatial inference is usually carried out by means of model-based techniques, which estimate the unde...
13 pages, 1 article*Exploratory Model Selection for Spatially Designed Experiments--Some Examples* (...
This dissertation consists of three papers written on the design and analysis of experiments in the ...
We consider robust methods for the construction of sampling designs in spatial studies. The designs ...
A standard objective in computer experiments is to approximate the behaviour of an unknown function ...
The methods of optimal design of experiments are considered for the regression problem when the obse...
Resolvable row–column designs are widely used in field trials to control variation and improve the p...
AbstractWhen inference regards a finite spatial pattern, a model-based framework is commonly used, e...
A practical problem in spatial statistics is that of constructing spatial sampling designs for envir...
International audienceThis work is devoted to the development of a new and efficient procedure for t...
When inference regards a finite spatial pattern, a model-based framework is commonly used, even if t...
Many applications in sensor networks require the estimation of spatial environmental fields. We focu...
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