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A comparison of design and model selection methods for supersaturated experiments
TLDR
This paper investigates the performance of a variety of design and model selection methods for supersaturated experiments through simulation studies. Expand
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Designs for Generalized Linear Models With Several Variables and Model Uncertainty
TLDR
A method is proposed for finding exact designs for such experiments that uses a criterion allowing for uncertainty in the link function, the linear predictor, or the model parameters, together with a design search. Expand
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Screening Strategies in the Presence of Interactions
TLDR
We provide the first comprehensive assessment and comparison of screening strategies for interactions using two-level supersaturated designs, group screening, and a variety of data analysis methods including shrinkage regression and Bayesian methods. Expand
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Bayesian Design of Experiments Using Approximate Coordinate Exchange
TLDR
We use a Gaussian process emulator to approximate the expected utility as a function of a single design coordinate in a series of conditional optimization steps. Expand
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Designs for Generalized Linear Models
This paper reviews the design of experiments for generalised linear models, including optimal design, Bayesian design and designs for models with random effects.
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D-OPTIMAL DESIGNS FOR POISSON REGRESSION MODELS
We consider the problem of finding an optimal design under a Poisson regression model with a log link, any number of independent variables, and an additive linear predictor. Local D-optimality of aExpand
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Robust designs for binary data: applications of simulated annealing
When the aim of an experiment is the estimation of a generalized linear model (GLM), standard designs from linear model theory may prove inadequate. This paper describes a flexible approach forExpand
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Emulation of Multivariate Simulators Using Thin-Plate Splines with Application to Atmospheric Dispersion
  • V. E. Bowman, D. Woods
  • Computer Science, Mathematics
  • SIAM/ASA J. Uncertain. Quantification
  • 23 December 2015
TLDR
We propose methodology to model multivariate output from a computer simulator taking into account output structure and fit a Gaussian process emulator to the coefficients of the resultant basis functions. Expand
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Design of experiments for screening
The aim of this paper is to review methods of designing screening experiments, ranging from designs originally developed for physical experiments to those especially tailored to experiments onExpand
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