23 citations · 60 across the 7 of their papers we have counts for
7 papers
Adaptive and robust experimental design for linear dynamical models using Kalman filter
Arno Strouwen, Bart M. Nicolaï, Peter Goos
Current experimental design techniques for dynamical systems often only incorporate measurement noise, while dynamical systems also involve process noise. To construct experimental…
A Note on the Output of a Coordinate-Exchange Algorithm for Optimal Experimental Design
Arno Strouwen, Peter Goos
The coordinate-exchange algorithm is commonly used to construct optimal experimental designs. Every execution of the coordinate-exchange algorithm produces a new, seemingly random,…
Bayesian D- and I-optimal designs for choice experiments involving mixtures and process variables
Mario Becerra, Peter Goos
Many food products involve mixtures of ingredients, where the mixtures can be expressed as combinations of ingredient proportions. In many cases, the quality and the consumer prefe…
Design and analysis of a microplate assay in the presence of multiple restrictions on the randomization
Alexandre Bohyn, Eric D. Schoen, Chee Ping Ng +4
Experiments using multi-step protocols often involve several restrictions on the randomization. For a specific application to in vitro testing on microplates, a design was required…
Enumeration of regular fractional factorial designs with four-level and two-level factors
Alexandre Bohyn, Eric D. Schoen, Peter Goos
Designs for screening experiments usually include factors with two levels only. Adding a few four-level factors allows for the inclusion of multi-level categorical factors or quant…
Bayesian I-optimal designs for choice experiments with mixtures
Mario Becerra, Peter Goos
Discrete choice experiments are frequently used to quantify consumer preferences by having respondents choose between different alternatives. Choice experiments involving mixtures…
Optimal Design of Experiments for Nonlinear Response Surface Models
Yuanzhi Huang, Steven Gilmour, Kalliopi Mylona +1
Many chemical and biological experiments involve multiple treatment factors and often it is convenient to fit a nonlinear model in these factors. This nonlinear model can be mechan…