ENBIS 2021 Spring Meeting

Session

Optimal DoE

1.2.2

17 May 2021, 11:15

Online

Conveners

Optimal DoE

• Grazia Vicario (DISMA - Politecnico di Torino)

23. Optimal designs for hypothesis testing in the presence of heterogeneous experimental groups

Marco Novelli

17/05/2021, 11:15

Data Science in Process Industries

Comparing the means of several experimental groups is an old and well known
problem in the statistical literature which arises in many application areas. In the
past decades, a large body of literature about the design of experiments for treatment
comparisons has flourished. However, the attention has been almost exclusively devoted
to estimation precision, and not to optimal testing. This...

39. Robust strategies to address the uncertainty of the response variable in Optimal Experimental Design

Mr Sergio Pozuelo-Campos (University of Castilla-La Mancha)

17/05/2021, 11:35

Data Science in Process Industries

The probability distribution of the response variable is one of the necessary assumptions in the design of an experiment and the existence of uncertainty supposes a challenge for practitioners. The aim of this work is the analysis of four strategies to obtain robust optimal designs in order to face this uncertainty. The strategies compared in this paper are compound criteria, multi-stage...

47. Adding points to D-optimal designs

Carlos de la Calle-Arroyo (Universidad de Castilla-La Mancha)

17/05/2021, 11:55

Data Science in Process Industries

One of the main criticisms to the optimal experimental design theory is that optimal designs tend to require too few points, frequently very extremal. In most of the models with one variable the number of different points reduces to the number of parameters to be estimated. Actually, an optimal design is used as a reference to measure how efficient are the designs used in practice. In this...