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Stochastic Models, Statistics and Their Applications: Dresden, Germany, March 2019 (Repost)

Posted By: AvaxGenius
Stochastic Models, Statistics and Their Applications: Dresden, Germany, March 2019 (Repost)

Stochastic Models, Statistics and Their Applications: Dresden, Germany, March 2019 by Ansgar Steland
English | EPUB | 2019 | 450 Pages | ISBN : 3030286649 | 33.1 MB

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.

Stochastic Models, Statistics and Their Applications: Dresden, Germany, March 2019 (Repost)

Posted By: AvaxGenius
Stochastic Models, Statistics and Their Applications: Dresden, Germany, March 2019 (Repost)

Stochastic Models, Statistics and Their Applications: Dresden, Germany, March 2019 by Ansgar Steland
English | PDF | 2019 | 450 Pages | ISBN : 3030286649 | 8.7 MB

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.