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.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
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 WrocławUniversity 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.
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.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: AwesomeBooks, Wallingford, Vereinigtes Königreich
hardcover. Zustand: Very Good. Stochastic Models, Statistics and Their Applications: Dresden, Germany, March 2019: 294 (Springer Proceedings in Mathematics & Statistics, 294) This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. . Artikel-Nr. 7719-9783030286644
Anzahl: 1 verfügbar
Anbieter: Bahamut Media, Reading, Vereinigtes Königreich
hardcover. Zustand: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee. Artikel-Nr. 6545-9783030286644
Anzahl: 1 verfügbar
Anbieter: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Deutschland
235 mm x 155 mm. XVI, 450 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Springer Proceedings in Mathematics & Statistics. Volume 294. Sprache: Englisch. Artikel-Nr. 1912LB
Anzahl: 2 verfügbar
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Buch. Zustand: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 468 pp. Englisch. Artikel-Nr. 9783030286644
Anzahl: 2 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume presents selected and peer-reviewed contributions from the 14thWorkshop 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. Artikel-Nr. 9783030286644
Anzahl: 1 verfügbar