Applications in Statistical Computing : From Music Data Analysis to Industrial Quality Improvement

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.

Nadja Bauer is a Lecturer at Dortmund University of Applied Sciences and Arts, Germany. Her research interests include industrial statistics, music data analysis and statistical education.

Katja Ickstadt is a Professor of Mathematical Statistics with Applications in Biometrics at the Faculty of Statistics, TU Dortmund University, Germany. Her main research areas include regression modeling and methods for biomedical applications, in particular from a Bayesian viewpoint.

Karsten Lübke is a Lecturer for Statistics and Mathematics at FOM University of Applied Science, Essen, Germany. His main research interests are in statistical education and data literacy.

Gero Szepannek is a Professor of Statistics and Business Mathematics at Stralsund University of Applied Sciences, Germany. Prior to this he worked for seven years at Santander as head of scoring and rating models. His main research interests are in machine learning,computational statistics, NLP, credit risk modeling and music information retrieval.

Heike Trautmann is a Professor of Information Systems and Statistics at the University of Münster, Germany and Director of the European Research Center for Information Systems (ERCIS). Her research chiefly focuses on data science, optimization, and automated algorithm selection.

Maurizio Vichi is a Full Professor of Statistics and Chair of the Department of Statistical Sciences at Sapienza University of Rome, Italy. He also serves as Coordinating Editor of the international journal Advances in Data Analysis and Classification, published by Springer. His research interests include statistical models for clustering, classification, dimensionality reduction, and new methods for official statistics.