TY - BOOK ID - 48303880 TI - Stochastic Models, Statistics and Their Applications : Dresden, Germany, March 2019 AU - Steland, Ansgar. AU - Rafajłowicz, Ewaryst. AU - Okhrin, Ostap. PY - 2019 SN - 3030286657 3030286649 PB - Cham : Springer International Publishing : Imprint: Springer, DB - UniCat KW - Stochastic processes KW - Statistics . KW - Probabilities. KW - Big data. KW - Econometrics. KW - Statistical Theory and Methods. KW - Probability Theory and Stochastic Processes. KW - Big Data. KW - Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. KW - Economics, Mathematical KW - Statistics KW - Data sets, Large KW - Large data sets KW - Data sets KW - Probability KW - Statistical inference KW - Combinations KW - Mathematics KW - Chance KW - Least squares KW - Mathematical statistics KW - Risk KW - Statistical analysis KW - Statistical data KW - Statistical methods KW - Statistical science KW - Econometrics UR - https://www.unicat.be/uniCat?func=search&query=sysid:48303880 AB - 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. ER -