Applications in Statistical Computing
From Music Data Analysis to Industrial Quality Improvement
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Beschreibung
This volume presents a selection of research papers on various topics at the interface of statistics and computer science. Emphasis is put on the practical applications of statistical methods in various disciplines, using machine learning and other computational methods. The book covers fields of research including the design of experiments, computational statistics, music data analysis, statistical process control, biometrics, industrial engineering, and econometrics. Gathering innovative, high-quality and scientifically relevant contributions, the volume was published in honor of Claus Weihs, Professor of Computational Statistics at TU Dortmund University, on the occasion of his 66th birthday.
This volume presents a selection of research papers on various topics at the interface of statistics and computer science. Emphasis is put on the practical applications of statistical methods in various disciplines, using machine learning and other computational methods. The book covers fields of research including the design of experiments, computational statistics, music data analysis, statistical process control, biometrics, industrial engineering, and econometrics. Gathering innovative, high-quality and scientifically relevant contributions, the volume was published in honor of Claus Weihs, Professor of Computational Statistics at TU Dortmund University, on the occasion of his 66th birthday.
Presents state-of-the-art research at the interface of statistics and computer science Contributes to two highly relevant research areas: data analysis and big data Covers applied fields of research such as industrial engineering, econometrics, biometrics, and music data analysis Published in honor of Claus Weihs, Professor of Computational Statistics at TU Dortmund University
Autor*in
Nadja Bauer
Themen in »Applications in Statistical Computing«
Statistical computing Data science Machine learning Computational statistics Classification Clustering Data analysis Big data Statistical process control Music data analysis Industrial engineering Industrial quality improvement Biometrics Econometrics Design of experiments