Collection
Algorithms, Analysis and Advanced Methodologies in the Design of Experiments
Topics covered:
Designing and analysing experiments is an integral part of the scientific process, both for discovery and verification. The methodology has been used in almost every scientific field such as biomedical, pharmaceutical, social science, engineering for conducting and analysing informative experiments that are time- and cost-effective. The advancement of statistical theory and methodology over the past years has resulted in many exciting new developments in the modern design of experiments, which are covered in this special issue. The papers in this issue cover both classical topics such as optimal design, computer experiments, clinical trials design, design algorithm, and factorial designs, and cutting-edging novel topics, such as sub data selection in big data analysis and online experiment.
Purpose of the issue:
The purpose of this issue is to stimulate a classical yet recently generative research area with both innovative methodological developments and important real-life applications in today’s world. The special issue brings together the current research interests and contribution of some of the leading contributors in this area.
Editors
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Min Yang
Min Yang is a Professor at the University of Illinois and an ASA fellow. He has developed novel algorithms and new framework of optimal designs and an efficient subdata selection in big data analysis, which have been recognized as ground-breaking work. The computer programs he developed for the clinical trial design have been used by many researchers at pharmaceutical companies and universities. He was invited to give a talk on dose-finding studies at FDA. Since 2003, his research has been continuously supported by NSF. In 2008, he was awarded NSF CAREER award, and cited by Amstat News as an up-and-comer, with five other junior statisticians.
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Pritam Ranjan
Dr. Ranjan is a Professor in Operations Management and Quantitative Techniques at Indian Institute of Management Indore. He was previously an Associate Professor in the department of Mathematics and Statistics at Acadia University, Canada. Dr. Ranjan obtained a Ph.D. degree in Statistics from Simon Fraser University, Canada. He is currently an associate editor for Canadian Journal of Statistics and has worked as an AE for JRSS(C), JSS and JQT. His primary research focus is in design and analysis of computer experiments, statistical modelling for computer simulators, sequential design for feature estimation.
