Highlights the latest advances in stochastic modeling, statistical inference and related applications
Features contributions on high-dimensional statistics, machine learning, big data, econometrics and time series, quality control, reliability and survival analysis
Addresses the needs of theoretical and applied researchers alike
Part of the book series: Springer Proceedings in Mathematics & Statistics (PROMS, volume 294)
Conference series link(s): SMSA: Workshop on Stochastic Models, Statistics and their Application
Conference proceedings info: SMSA 2019.
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Table of contents (33 papers)
Theory and Related Topics
Stochastic Models, Statistics and Their Applications
About this book
This volume presents selected and peer-reviewed contributions from the 14th Workshop on Stochastic Models, Statistics and Their Applications, held in Dresden, Germany, on March 6-8, 2019. Addressing the needs of theoretical and applied researchers alike, the contributions provide an overview of the latest advances and trends in the areas of mathematical statistics and applied probability, and their applications to high-dimensional statistics, econometrics and time series analysis, statistics for stochastic processes, statistical machine learning, big data and data science, random matrix theory, quality control, change-point analysis and detection, finance, copulas, survival analysis and reliability, sequential experiments, empirical processes, and microsimulations. As the book demonstrates, stochastic models and related statistical procedures and algorithms are essential to more comprehensively understanding and solving present-day problems arising in e.g. the natural sciences, machine learning, data science, engineering, image analysis, genetics, econometrics and finance.
- high-dimensional statistics
- statistics for stochastic processes
- stochastic models
- big data
- machine learning
- data science
- survival analysis
- nonparameteric estimation
- change points and detection
- random fields
- reliability theory
Editors and Affiliations
Institute of Statistics, RWTH Aachen University, Aachen, Germany
Department of Control Systems and Mechatronics, Wrocław University of Technology, Wrocław, Poland
Institute of Transport and Economics, Technische Universität Dresden, Dresden, Germany
About the editors
Ansgar Steland received his Ph.D. in Mathematics from the University of Göttingen, Germany. After positions at the Technische Universität Berlin as a consultant, at the European University Viadrina and the Ruhr-University of Bochum, he joined the faculty of RWTH Aachen University, Germany, where he was appointed Full Professor at the Institute of Statistics in 2006. He is an Elected Member of the International Statistical Institute (ISI); Chair of the Society for Reliability, Quality and Safety; and Chair of the German Statistical Society’s Statistics in Natural Sciences and Technology Section. His main research interests are in change detection and quality control, high-dimensional statistics, time series analysis, nonparametric statistics, and image analysis and its applications to econometrics, the natural sciences and engineering, especially photovoltaics.
Ewaryst Rafajłowicz received his Ph.D. and D.Sc. degrees in Control Theory from Wrocław University of Technology, Poland. In 1996 he became a Full Professor, and in 2016 he was elected to the Polish Academy of Sciences as a Corresponding Member. He has been a Visiting Professor at many universities in the USA, Canada, Germany and England and has published ca. 150 papers on the identification of distributed-parameter systems, optimal design of experiments, signal processing, neural networks, nonparametric regression estimation, statistical quality control and image processing. In addition, he has served on the program committees of several international conferences and as a reviewer for many journals.
Ostap Okhrin is a Professor of Econometrics and Statistics at the Technische Universität Dresden, Germany. He worked at the European University Viadrina and later was an Assistant and then Associate Professor for Statistics of Financial Markets at the Humboldt-Universität zu Berlin and one of the principal investigators of the CRC-649 (Collaborative Research Center) “Economic Risk.” He currently teaches multivariate, computational and mathematical statistics, and his research focuses on multivariate models, in particular in copulas and financial econometrics.
Book Title: Stochastic Models, Statistics and Their Applications
Book Subtitle: Dresden, Germany, March 2019
Editors: Ansgar Steland, Ewaryst Rafajłowicz, Ostap Okhrin
Series Title: Springer Proceedings in Mathematics & Statistics
Publisher: Springer Cham
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-28664-4Published: 16 October 2019
Softcover ISBN: 978-3-030-28667-5Published: 16 October 2020
eBook ISBN: 978-3-030-28665-1Published: 15 October 2019
Series ISSN: 2194-1009
Series E-ISSN: 2194-1017
Edition Number: 1
Number of Pages: XVI, 450
Number of Illustrations: 39 b/w illustrations, 46 illustrations in colour