Special Issue on Experimental Design
This Special Issue focuses on significant and original articles in experimental design. The emphasis is on promoting the development and use of statistical methodology in experimental design to solve complicated problems in such areas as linear mixed effect models, software systems, recommender systems, clinical trials, randomized trials, reinforcement learning, and other similar fields. The Special Issue contains nine research papers on experiment design, including sequential and non-sequential designs, sample size and power analysis, kernel density estimation, optimal population design, and combinatorial testing.
Edited by
Xinwei Deng(Dept. of Statistics, College of Science, Virginia Tech, USA)
Devon Lin(Dept. of Mathematics and Statistics, Queen‘s University, Canada)