Statistical Quality Technologies: Theory and Practice (ICSA Book Series in Statistics)

Name: Statistical Quality Technologies: Theory and Practice (ICSA Book Series in Statistics)
ISBN: 9783030207083

Language: English

Published by Springer, 2019

3030207080 / 9783030207083

Series: Book 17 of 19 - ICSA Book Series in Statistics

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Title: Statistical Quality Technologies: Theory and Practice (ICSA Book Series in Statistics)
Publisher: Springer
Publication year: 2019
Condition: Very Good
Binding: hardcover
Language: English
ISBN 10: 3030207080
ISBN 13: 9783030207083
Series: Book 17 of 19: ICSA Book Series in Statistics

About the Author

Yuhlong Lio is a professor in the Department of Mathematical Science at the University of South Dakota. His research interest is in theoretical and methodology developments in mathematics and includes reliability inferences, kernel-smooth estimation, and mathematical modeling. Dr. Lio has been invited as a referee to review papers for more than 30 international and peer-review journals including Applied Mathematics and Computation, Applied Mathematical Modeling, Journal of Quality Technology and IEEE Transactions on Reliability, among others. Dr. Lio currently serves on the advisory board for Journal of Statistics and Mathematics and as associate editor for Journal of Statistical Computation and Simulation and Electronic Journal of Applied Statistical Analysis. Dr. Lio received his BS in mathematics from Nation Cheng Kung University, Taiwan, his MS in mathematics from National Central University, Taiwan, and his PhD. in Statistics from University of South Carolina, USA.

Hon Keung Tony Ng is a professor of statistical science with the Southern Methodist University, Dallas, TX, USA. He is an associate editor of Communications in Statistics, Computational Statistics, IEEE Transactions on Reliability, Journal of Statistical Computation and Simulation, Naval Research Logistics, Sequential Analysis and Statistics and Probability Letters. His research interests include reliability, censoring methodology, ordered data analysis, nonparametric methods, and statistical inference. He has published more than 100 research papers in refereed journals. He is the co-author of the book Precedence-Type Tests and Applications (2006, with Balakrishnan) and co-editor of Ordered Data Analysis, Modeling and Health Research Methods (Springer 2015, ed. with Choudhary, Nagaraja). Professor Ng is a fellow of the American Statistical Association,an elected senior member of IEEE and an elected member of the International Statistical Institute.

Tzong-Ru Tsai is the dean of the College of Business and Management and a professor in the Department of Statistics at Tamkang University in New Taipei City, Taiwan. His main research interests include quality control and reliability analysis. He has served as a consultant with extensive expertise in statistical quality control, reliability assessment on highly reliable products, and design of experiments for many companies in the past years. He is an associate editor of the Journal of Statistical Computation and Simulation. Dr. Tsai has been invited as a referee to review papers for more than 20 peer-review journals, including IEEE Transactions on Reliability, Quality Engineering, and Quality and Reliability Engineering International. He has published more than 70 research papers in refereed journals.

Ding-Geng (Din) Chen is the Wallace H. Kuralt Distinguished Professor and Director of the Consortium for Statistical Development and Consultation (CSDC) in the School of Social Work, and is jointly appointed as a clinical professor in the Department of Biostatistics at the UNC Gillings School of Global Health. He is an elected fellow of American Statistical Association. As a professor in biostatistics, he is interested in developing biostatistical methodologies in clinical trials, meta-analysis, Bayesian statistics and their applications to public health. As a professor in social work, he is interested in developing Bayesian social and health intervention research, cusp catastrophe modelling, statistical causal inferences, propensity score and structural-equation models (SEM). He is PI/Co-PI for several NIH R01 research projects in biostatistical methodology development and public health applications.

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