书目名称 | Stochastic Models, Statistics and Their Applications | 副标题 | Dresden, Germany, Ma | 编辑 | Ansgar Steland,Ewaryst Rafajłowicz,Ostap Okhrin | 视频video | | 概述 | Highlights the latest advances in stochastic modeling, statistical inference and related applications.Features contributions on high-dimensional statistics, machine learning, big data, econometrics an | 丛书名称 | Springer Proceedings in Mathematics & Statistics | 图书封面 |  | 描述 | .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. . | 出版日期 | Conference proceedings 2019 | 关键词 | high-dimensional statistics; statistics for stochastic processes; stochastic models; big data; machine l | 版次 | 1 | doi | https://doi.org/10.1007/978-3-030-28665-1 | isbn_softcover | 978-3-030-28667-5 | isbn_ebook | 978-3-030-28665-1Series ISSN 2194-1009 Series E-ISSN 2194-1017 | issn_series | 2194-1009 | copyright | Springer Nature Switzerland AG 2019 |
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