ENBIS-22 Trondheim Conference

Session

CONTRIBUTED Design of Experiment 4

28 Jun 2022, 11:30

EL6

Conveners

CONTRIBUTED Design of Experiment 4

• Hendry Raharjo (Chalmers University)

20. Generative models and Bayesian inversion using Laplace approximation

Dr Manuel Marschall (Physikalisch-Technische Bundesanstalt)

28/06/2022, 11:30

Design and analysis of experiments

Solving inverse problems with the Bayesian paradigm relies on a sensible choice of the prior. Elicitation of expert knowledge and formulation of physical constraints in a probabilistic sense is often challenging. Recently, the advances made in machine leaning and statistical generative models have been used to develop novel approaches to Bayesian inference relying on data-driven and highly...

39. Minimal sample size in balanced ANOVA models and its calculation using the R package ``miniSize''

Dr Bernhard Spangl (University of Natural Resources and Life Sciences, Vienna)

28/06/2022, 11:50

Design and analysis of experiments

We consider balanced one-way, two-way, and three-way ANOVA models to test the hypothesis that the fixed factor A has no effect. The other factors are fixed or random. We determine the noncentrality parameter for the exact F-test, describe its minimal value by a sharp lower bound, and thus we can guarantee the worst-case power for the F-test. These results allow us to compute the minimal sample...

102. What makes a car detailing job great? – Adaptive Multi-Stage Customer DOE

Zhiwu Liang (P&G)

28/06/2022, 12:10

Design and analysis of experiments

Car detailing is a tough job. Transforming a car from a muddy, rusty, full of pet fur box-on-wheels into a like-new clean and shiny ride takes a lot of time, specialized products and a skilled detailer.
But…what does the customer really appreciate on such a detailed car cleaning and restoring job? Are shiny rims most important for satisfaction? Interior smell? A shiny waxed hood? It is...