Overview
- Focuses on modern methods for statistical learning and modeling in data analysis
- Presents real-world applications in medicine, finance, engineering, marketing and cyber risk
- Will appeal to researchers and practitioners alike
Part of the book series: Studies in Classification, Data Analysis, and Knowledge Organization (STUDIES CLASS)
Included in the following conference series:
Conference proceedings info: CLADAG 2019.
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Table of contents (18 papers)
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Front Matter
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Statistical Learning and Modeling in Data Analysis
Keywords
About this book
The contributions gathered in this book focus on modern methods for statistical learning and modeling in data analysis and present a series of engaging real-world applications. The book covers numerous research topics, ranging from statistical inference and modeling to clustering and factorial methods, from directional data analysis to time series analysis and small area estimation. The applications reflect new analyses in a variety of fields, including medicine, finance, engineering, marketing and cyber risk.
The book gathers selected and peer-reviewed contributions presented at the 12th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2019), held in Cassino, Italy, on September 11–13, 2019. CLADAG promotes advanced methodological research in multivariate statistics with a special focus on data analysis and classification, and supports the exchange and dissemination of ideas, methodological concepts, numerical methods, algorithms, and computational and applied results. This book, true to CLADAG’s goals, is intended for researchers and practitioners who are interested in the latest developments and applications in the field of data analysis and classification.Editors and Affiliations
About the editors
Simona Balzano is an Assistant Professor of Statistics at the University of Cassino and Southern Lazio, Italy, where she teaches on data analysis and research methods in management. Her recent research activities concern multivariate analysis, partial least squares regression and path-modeling, and structural equation modeling. Her interests include applications in performance analysis, consumer analysis, and other related fields of business and industry.
Giovanni C. Porzio is a Professor of Statistics at the University of Cassino and Southern Lazio, Italy, where he has previously served as Department Head and Director of Graduate Studies in Economics. His research interests include directional statistics, statistical learning, nonparametric multivariate analysis and data depth, graphical methods and data visualization. His research work has appeared in several journals and books.
Renato Salvatore is an Assistant Professor of Economic Statistics at the University of Cassino and Southern Lazio, Italy. He has co-authored papers, book chapters, and proceedings on sampling surveys, small area estimation, and multivariate analysis. In addition, he has been co-editor of several conference proceedings, and currently teaches on economic statistics and market analysis.
Domenico Vistocco is an Associate Professor of Statistics at the University of Naples Federico II, Italy. He is an Associate Editor of Computational Statistics and Editorial Manager of Statistica Applicata - Italian Journal of Applied Statistics. He has co-authored two books on quantile regression and ca. 100 papers, book chapters, proceedings, post-proceedings and editorials on various statistical topics. He teaches on statistical inference, data analysis, applied statistics and statistical programming. His research interests include quantile regression, computational statistics, statistical models, exploratory data analysis and visualization.
Maurizio Vichi is a Professor of Statistics and Chair of the Department of Statistical Sciences at Sapienza University of Rome, Italy. He is also Coordinating Editor of the international journal Advances in Data Analysis and Classification and Acting Chair of the European Statistical Advisory Committee of the EU. He teaches on multivariate statistics and data analysis and statistical modeling. His research interests include statistical models for clustering, classification, dimensionality reduction, composite indicators, PLS, SEM and new methods for official statistics based on smart statistics and big data analysis. He is the author of more than 150 papers, mainly published in peer-reviewed international statistics journals.
Bibliographic Information
Book Title: Statistical Learning and Modeling in Data Analysis
Book Subtitle: Methods and Applications
Editors: Simona Balzano, Giovanni C. Porzio, Renato Salvatore, Domenico Vistocco, Maurizio Vichi
Series Title: Studies in Classification, Data Analysis, and Knowledge Organization
DOI: https://doi.org/10.1007/978-3-030-69944-4
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2021
Softcover ISBN: 978-3-030-69943-7Published: 14 July 2021
eBook ISBN: 978-3-030-69944-4Published: 13 July 2021
Series ISSN: 1431-8814
Series E-ISSN: 2198-3321
Edition Number: 1
Number of Pages: VIII, 182
Number of Illustrations: 14 b/w illustrations, 26 illustrations in colour
Topics: Statistical Theory and Methods, Statistics and Computing/Statistics Programs, Data Mining and Knowledge Discovery, Applied Statistics, Machine Learning, Data Structures and Information Theory