In the statistical domain, certain topics have received considerable attention during the last decade or so, necessitated by the growth and evolution of data and theoretical challenges. This growth has invariably been accompanied by computational advancement, which has presented end users as well as researchers with the necessary opportunities to handle data and implement modelling solutions for statistical purposes.
Showcasing the interplay among a variety of disciplines, this book offers pioneering theoretical and applied solutions to practice-oriented problems. As a carefully curated collection of prominent international thought leaders, it fosters collaboration between statisticians and biostatisticians and provides an array of thought processes and tools to its readers. The book thereby creates an understanding and appreciation of recent developments as well as an implementation of these contributions within the broader framework of both academia andindustry.
Computational and Methodological Statistics and Biostatistics is composed of three main themes:
• Recent developments in theory and applications of statistical distributions;
• Recent developments in supervised and unsupervised modelling;
• Recent developments in biostatistics;
and also features programming code and accompanying algorithms to enable readers to replicate and implement methodologies. Therefore, this monograph provides a concise point of reference for a variety of current trends and topics within the statistical domain. With interdisciplinary appeal, it will be useful to researchers, graduate students, and practitioners in statistics, biostatistics, clinical methodology, geology, data science, and actuarial science, amongst others.
Dr. Andriėtte Bekker is a professor and the current head of the Department of Statistics at the Faculty of Natural and Agricultural Sciences, at the University of Pretoria. Her expertise lies in statistical distribution theory and comprises the study, development and expansion of distributions, and the addressing of parametric statistical inferential aspects, within the classical as well as the Bayesian framework. She is the academic research leader of the Statistical Theory and Applied Statistics focus area within the Department of Science and Technology/ National Research Foundation (DST-NRF) Centre of Excellence in Mathematical and Statistical Sciences, as well as an elected member of the International Statistical Institute. Dr. Bekker has published more than 70 peer-reviewed papers in fundamental statistical research.
Dr. Ding-Geng Chen is a fellow of American Statistical Association and currently the Wallace Kuralt distinguished professor at the University of North Carolina at Chapel Hill as well as the South Africa DST-NRF-SAMRC, SARChI in Biostatistics (Tier 1). He was a professor in biostatistics at the University of Rochester and the Karl E. Peace endowed eminent scholar chair in biostatistics at Georgia Southern University. He is also a senior statistics consultant for biopharmaceuticals and government agencies with extensive expertise in Monte-Carlo simulations, clinical trial biostatistics and public health statistics. Dr. Chen has more than 150 referred professional publications and co-authored and co-edited twenty-three books on clinical trial methodology, meta-analysis and public health applications. He has been invited nationally and internationally to give speeches on his research.
Dr. Johan Ferreira is currently a senior lecturer in the Department of Statistics at the University of Pretoria, South Africa, and is Junior Focus Area Coordinator for the Statistical Theory and Applied Statistics focus area ofthe Centre of Excellence in Mathematical and Statistical Science based at the University of the Witwatersrand in Johannesburg. He regularly publishes in accredited peer-reviewed journals and reviews manuscripts for international journals. He is an ASLP 4.1/4.2 fellow of Future Africa and has been identified as one of the Top 200 South Africans under the age of 35 by the Mail & Guardian newspaper in the Education category in 2016.
