Distribution-Free Methods for Statistical Process Monitoring and Control - Softcover

Über die Autorin bzw. den Autor

Markos V. Koutras is a Full Professor at the Department of Statistics and Insurance Science, University of Piraeus, Greece. He received his B.S. in Mathematics and holds an M.Sc. in Computer Science and Operations Research and a Ph.D. in Statistics. He has authored more than 90 publications in referred journals, 20 publications in referred special volumes (by invitation). He has authored/co-authored 10 books in Greek and 5 in English (2 of them forthcoming). He currently serves on the editorial board of several journals (Annals of the Institute of Statistical Mathematics, Methodology and Computing in Applied Probability, Communications in Statistics etc) and he has been reviewer for more than 35 Journals. His research interests include the theory of run and scan statistics, statistical process control, reliability theory, nonparametric statistics and multivariate statistical analysis. 

Ioannis S. Triantafyllou is an Assistant Professor at the Department of Computer Science and Biomedical Informatics, University of Thessaly, Greece. He received his B.S. degree in Mathematics from the University of Athens, Greece, and his M.Sc. and Ph.D. degrees in Statistics from the University of Piraeus, Greece. He has published over 40 peer-reviewed papers in international refereed scientific journals, edited volumes and conference proceedings, and has served as referee for more than 15 scientific journals. His research interests include applied probability, nonparametric statistics, reliability theory and statistical process control.

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This book explores nonparametric statistical process control. It provides an up-to-date overview of nonparametric Shewhart-type univariate control charts, and reviews the recent literature on nonparametric charts, particularly multivariate schemes. Further, it discusses observations tied to the monitored population quantile, focusing on the Shewhart Sign chart. The book also addresses the issue of practically assuming the normality and the independence when a process is statistically monitored, and examines in detail change-point analysis-based distribution-free control charts designed for Phase I applications. Moreover, it introduces six distribution-free EWMA schemes for simultaneously monitoring the location and scale parameters of a univariate continuous process, and establishes two nonparametric Shewhart-type control charts based on order statistics with signaling runs-type rules. Lastly, the book proposes novel and effective method for early disease detection.