ENBIS-23 Valencia Conference

Session

CONTRIBUTED Design of Experiments 1

11 Sept 2023, 13:30

2.7/2.8

Conveners

CONTRIBUTED Design of Experiments 1

• Jacqueline Asscher (Kinneret College)

22. Brownie Bee: An Appetizing Way to Implement Bayesian Optimization in Companies

Dr Morten Bormann Nielsen (Danish Technological Institute)

11/09/2023, 13:30

Design and analysis of experiments

Design of Experiments (DOE) is a powerful tool for optimizing industrial processes with a long history and impressive track record. However, despite its success in many industries, most businesses in Denmark still do not use DOE in any form due to a lack of statistical training, preference for intuitive experimentation, and misconceptions about its effectiveness.

To address this issue, the...

59. A Model-Robust Subsampling Approach in Presence of Outliers

Prof. Laura Deldossi (Università Cattolica del Sacro Cuore)

11/09/2023, 13:50

Design and analysis of experiments

Abstract
In the era of big data, several sampling approaches are proposed to reduce costs (and time) and to help in informed decision making. Most of these proposals require the specification of a model for the big data. This model assumption, as well as the possible presence of outliers in the big dataset, represent a limitation for the most commonly applied subsampling criterions.
The task...

163. Optimal Design for Model Autocompletion

Arno Strouwen

11/09/2023, 14:10

Design and analysis of experiments

Most experimental design methodology focuses on parameter precision, where the model structure is assumed known and fixed. But arguably, finding the correct model structure is the part of the modelling process that takes the most effort.

Experimental design methodology for model discrimination usually focuses on discriminating between two or more known model structures. But often part of...