© 2019

Stochastic Models, Statistics and Their Applications

Dresden, Germany, March 2019

  • Ansgar Steland
  • Ewaryst Rafajłowicz
  • Ostap Okhrin
Conference proceedings SMSA 2019

Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 294)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Plenary Lectures

    1. Front Matter
      Pages 1-1
    2. Winfried Stute
      Pages 3-11
    3. Irène Gijbels, Rezaul Karim, Anneleen Verhasselt
      Pages 13-40
    4. Mathias Mørck Ljungdahl, Mark Podolskij
      Pages 41-56
  3. Theory and Related Topics

    1. Front Matter
      Pages 57-57
    2. Eckhard Liebscher
      Pages 111-120
    3. Zdeněk Hlávka, Marie Hušková
      Pages 143-155
    4. Boris Darkhovsky, Alexandra Piryatinska
      Pages 157-176
    5. Qinghua Liu, Rui Zhang, Yao Xie
      Pages 177-192
    6. Christian H. Weiß
      Pages 239-250
  4. Stochastic Models, Methods and Simulations

    1. Front Matter
      Pages 267-267
    2. Jan Pablo Burgard, Joscha Krause, Hariolf Merkle, Ralf Münnich, Simon Schmaus
      Pages 269-290
    3. Maria Eduarda Silva, Isabel Silva, Cristina Torres
      Pages 291-303
    4. E. Gonçalves, N. Mendes-Lopes
      Pages 305-314
    5. Johannes Bracher
      Pages 323-333
    6. Sebastian Büscher, Manuel Batram, Dietmar Bauer
      Pages 335-349
    7. Undine Falkenhagen, Wolfgang Kössler, Hans-J. Lenz
      Pages 351-359
  5. Applications and Algorithms

    1. Front Matter
      Pages 361-361
    2. Antoine Tordeux, Mohcine Chraibi, Armin Seyfried, Andreas Schadschneider
      Pages 363-372
    3. Artur Gramacki, Marek Kowal, Małgorzata Mazurkiewicz, Jarosław Gramacki, Anna Pławiak-Mowna
      Pages 373-383
    4. Przemysław Śliwiński, Paweł Wachel, Adrian Gałęziowski
      Pages 385-392
    5. Sarah Krömer, Wolfgang Stummer
      Pages 393-407
  6. Back Matter
    Pages 449-450

About these proceedings


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 econometrics copulas simulations data science survival analysis nonparameteric estimation change points and detection random fields reliability theory algorithms

Editors and affiliations

  • Ansgar Steland
    • 1
  • Ewaryst Rafajłowicz
    • 2
  • Ostap Okhrin
    • 3
  1. 1.Institute of StatisticsRWTH Aachen UniversityAachenGermany
  2. 2.Department of Control Systems and MechatronicsWrocław University of TechnologyWrocławPoland
  3. 3.Institute of Transport and EconomicsTechnische Universität DresdenDresdenGermany

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.

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