Statistical Learning and Modeling in Data Analysis: Methods and Applications - Brossura

Brossura

ISBN 10: 3030699439 ISBN 13: 9783030699437

Casa editrice: Springer, 2021

Riassunto

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.

Su questo libro

Informazioni sull?autore

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.

Dalla quarta di copertina

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.

Dettagli dell'edizione

• Editore: Springer
• Data di pubblicazione: 2021
• Lingua: Inglese
• ISBN 10: 3030699439
• ISBN 13: 9783030699437
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 192
• Redattore: Balzano Simona, Porzio Giovanni C., Salvatore Renato, Vistocco Domenico, Vichi Maurizio
• Contatto del produttore: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Germania