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Simona Balzano - Statistical Learning and Modeling in Data Analysis: Methods and Applications

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Simona Balzano Statistical Learning and Modeling in Data Analysis: Methods and Applications

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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 1113, 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 CLADAGs goals, is intended for researchers and practitioners who are interested in the latest developments and applications in the field of data analysis and classification.

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Contents
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Book cover of Statistical Learning and Modeling in Data Analysis Studies in - photo 1
Book cover of Statistical Learning and Modeling in Data Analysis
Studies in Classification, Data Analysis, and Knowledge Organization
Editorial Board
Daniel Baier
Bayreuth, Germany
Frank Critchley
Milton Keynes, UK
Reinhold Decker
Bielefeld, Germany
Edwin Diday
Paris, France
Michael Greenacre
Barcelona, Spain
Carlo Natale Lauro
Naples, Italy
Jacqueline Meulman
Leiden, The Netherlands
Paola Monari
Bologna, Italy
Shizuhiko Nishisato
Toronto, Canada
Noboru Ohsumi
Tokyo, Japan
Otto Opitz
Augsburg, Germany
Gunter Ritter
Passau, Germany
Martin Schader
Mannheim, Germany
Managing Editors
Wolfgang Gaul
Karlsruhe, Germany
Maurizio Vichi
Rome, Italy
Claus Weihs
Dortmund, Germany

Studies in Classification, Data Analysis, and Knowledge

Organization is a book series which offers constant and up-to-date information on the most recent developments and methods in the fields of statistical data analysis, exploratory statistics, classification and clustering, handling of information and ordering of knowledge. It covers a broad scope of theoretical, methodological as well as application-oriented articles, surveys and discussions from an international authorship and includes fields like computational statistics, pattern recognition, biological taxonomy, DNA and genome analysis, marketing, finance and other areas in economics, databases and the internet. A major purpose is to show the intimate interplay between various, seemingly unrelated domains and to foster the cooperation between mathematicians, statisticians, computer scientists and practitioners by offering well-based and innovative solutions to urgent problems of practice.

More information about this series at http://www.springer.com/series/1564

Editors
Simona Balzano , Giovanni C. Porzio , Renato Salvatore , Domenico Vistocco and Maurizio Vichi
Statistical Learning and Modeling in Data Analysis
Methods and Applications
1st ed. 2021
Logo of the publisher Editors Simona Balzano Department of Economics and - photo 2
Logo of the publisher
Editors
Simona Balzano
Department of Economics and Law, University of Cassino and Southern Lazio, Cassino, Italy
Giovanni C. Porzio
Department of Economics and Law, University of Cassino and Southern Lazio, Cassino, Italy
Renato Salvatore
Department of Economics and Law, University of Cassino and Southern Lazio, Cassino, Italy
Domenico Vistocco
Department of Political Science, University of Naples Federico II, Naples, Italy
Maurizio Vichi
Department of Statistical Sciences, Sapienza University of Rome, Rome, Italy
ISSN 1431-8814 e-ISSN 2198-3321
Studies in Classification, Data Analysis, and Knowledge Organization
ISBN 978-3-030-69943-7 e-ISBN 978-3-030-69944-4
https://doi.org/10.1007/978-3-030-69944-4
Mathematics Subject Classication (2010): 62-06 62-07 62Fxx 62Gxx 62Hxx 62Jxx 62Kxx
Springer Nature Switzerland AG 2021
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This Springer imprint is published by the registered company Springer Nature Switzerland AG

The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

This book offers a collection of papers focusing on methods for statistical learning and modeling in data analysis. A series of interesting applications are offered as well. Several research topics are covered, ranging from statistical inference and modeling to clustering and factorial methods, from directional data analysis to time series analysis and small area estimation. Applications deal with new analyses within a variety of fields of interest: medicine, finance, engineering, marketing, cyber risk, to cite a few.

The book arises as post-proceedings of the 12th meeting of the CLAssification and Data Analysis Group (CLADAG) of the Italian Statistical Society (SIS), held in Cassino (IT), on September 1113, 2019. The first CLADAG meeting was held in 1997, in Pescara (IT). CLADAG is also a member of the International Federation of Classification Societies (IFCS), founded in 1985. CLADAG promotes advanced methodological research in multivariate statistics with a special vocation towards Data Analysis and Classification. It supports the interchange of ideas in these fields of research, including the dissemination of concepts, numerical methods, algorithms, computational and applied results. This book is thus in line with the main CLADAG goals.

Thanks to the participation of renowned speakers, coming from 28 different countries, the scientific program of the CLADAG 2019 Conference was particularly engaging. It saw 5 Keynote Lectures, 32 Invited Sessions, 16 Contributed Sessions, a Round Table, and a Data Competition. The richness of the Conference program, and hence of this book, is definitely due to the Conference Scientific Committee and particularly to its Chair Francesca Greselin. We are indebted to their work. We are also indebted to the anonymous referees. They did a great job and helped us to improve the overall quality of this book.

Our gratitude also goes to the staff of the Department of Economics and Law, University of Cassino and Southern Lazio, who supported the conference and contributed to its success. A special thank goes to Livia Iannucci, who worked side by side with the Local Organizing Committee offering her precious administrative support before, during, and after the conference.

Above all, we are thankful to all the participants and to those who, among them, have chosen this book to share their research findings. Our wish is that this book will contribute to foster the creation of new knowledge in the field.

Simona Balzano
Giovanni C. Porzio
Renato Salvatore
Domenico Vistocco
Maurizio Vichi
Cassino, Italy
26 November 2020
Contents
Alan Agresti , Claudia Tarantola and Roberta Varriale
Anthony C. Atkinson , Marco Riani , Aldo Corbellini and Gianluca Morelli
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