01. Design and Analysis of Experiments

TL;DR: In this paper, a multi-objective optimization is employed to determine the optimum operating temperature and pressure in an industrial process of toluene production as a solvent, while carbon dioxide emission has also been taken into account as the environmental function that is optimized to acquire a cleaner production line.

TL;DR: In this article , a graph-based MOCU-based Bayesian optimization framework is proposed to achieve a scalable objective-based experimental design, which takes the main objective of the process into account during the experimental design process.

TL;DR: In this article, the authors present experimental and numerical analyses dealing with the influence of tyre properties on the stability of weave and wobble in straight running on a sport-touring motorcycle equipped with sensors.

TL;DR: In this paper, the authors proposed a budget-split design for online A/B testing, which is unbiased in any marketplace where buyers have a finite or infinite budget, and showed that it is more powerful than all other unbiased designs in the literature.

TL;DR: In this paper, it is shown that Tukey's test of additivity is equivalent to the test of a regression coefficient in a model with a single covariate, and the derivation given is general for the standard experimental designs, such as complete and incomplete randomized blocks and Latin squares.

TL;DR: In this paper, the authors provide a detailed discussion of the calculation of sample sizes using the width of confidence intervals for pairwise comparisons, treatment-versus-control comparisons, trends, and difference of averages.

TL;DR: In this article, an alternate formula for computing the adjusted treatment sum of squares for Group Divisible Partially Balanced Incomplete Block Designs (GD-PBIB) was proposed.

TL;DR: The authors summarize information scattered in the technical literature on a subject too new to be included in most textbooks, but which is of interest to statisticians, and those who use statistics in science and education, at an advanced undergraduate or higher level.