Statistical Learning and Modeling in Data Analysis
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.
|Reihe||Studies in Classification, Data Analysis, and Knowledge Organization|
|Ausgabe||1st ed. 2021|
|Genre||Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik|
|Verlag||Springer International Publishing|
|Herausgegeben von||Simona Balzano, Giovanni C. Porzio, Renato Salvatore, Domenico Vistocco, Maurizio Vichi|