Optimal Experimental Design: A Concise Introduction for Researchers

This textbook provides a concise introduction to optimal experimental design and efficiently prepares the reader for research in the area. It presents the common concepts and techniques for linear and nonlinear models as well as Bayesian optimal designs. The last two chapters are devoted to particular themes of interest, including recent developments and hot topics in optimal experimental design, and real-world applications. Numerous examples and exercises are included, some of them with solutions or hints, as well as references to the existing software for computing designs. The book is primarily intended for graduate students and young researchers in statistics and applied mathematics who are new to the field of optimal experimental design. Given the applications and the way concepts and results are introduced, parts of the text will also appeal to engineers and other applied researchers.

Jesús López-Fidalgo is a Full professor at the University of Navarre in Pamplona, Spain, where he is the Director of the Institute of Data Science and Artificial Intelligence and the Master in Big Data Science. An Elected Member of the International Statistical Institute, he was the President of the Spanish Society of Statistics and Operations Research and the Editor-in-Chief of the journal TEST. In addition, he was co-founder of the National Biostatistics Network, the Dean of the Industrial Engineering School at the University of Castilla-La Mancha, and he managed the National Plan for Mathematics within the Spanish Ministry of Science and Innovation. He has published more than 100 papers in academic journals and has written several books, including ＂El azar no existe＂ (Randomness Does not Exist). His research interests include optimal experimental design, statistical modelling and data science. He also devotes his time to statistical consulting in different areas, including engineering, medicine, pharmacokinetics, biology and genomics, and to the popularization of science and statistics in particular.