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A comparison of design and model selection methods for supersaturated experiments
Designs for Generalized Linear Models With Several Variables and Model Uncertainty
A method is proposed for finding exact designs for experiments that uses a criterion allowing for uncertainty in the link function, the linear predictor, or the model parameters, together with a design search.
Screening Strategies in the Presence of Interactions
This article gives 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.
Bayesian Design of Experiments Using Approximate Coordinate Exchange
This work provides the most general solution to date for decision-theoretical Bayesian design through a novel approximate coordinate exchange algorithm that uses a Gaussian process emulator to approximate the expected utility as a function of a single design coordinate in a series of conditional optimization steps.
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.
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 on…
Multifactor B-Spline Mixed Models in Designed Experiments for the Engine Mapping Problem
Multifactor B-spline regression models are described that have useful properties for designing experiments, including the advantage that linear model theory applies.
Robust designs for binary data: applications of simulated annealing
- D. Woods
- 1 January 2010
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 for…
Multivariate emulation of computer simulators: model selection and diagnostics with application to a humanitarian relief model
- Antony M. Overstall, D. Woods
- Computer ScienceJournal of the Royal Statistical Society. Series…
- 15 June 2015
We present a common framework for Bayesian emulation methodologies for multivariate output simulators, or computer models, that employ either parametric linear models or non‐parametric Gaussian…
Emulation of Multivariate Simulators Using Thin-Plate Splines with Application to Atmospheric Dispersion
This work proposes methodology to model multivariate output from a computer simulator taking into account output structure in the responses, and develops methodology for the two thin-plate spline emulators, which significantly outperform the principal component emulator.