Francesca Martella – författare

This last of four volumes on Statistical Science: From Theory to Applied Research presents peer-reviewed short papers on theoretical and applied statistics presented at the Joint Meeting SIS-FENStatS 2026, held in Rome, Italy, on June 22–25, 2026. The meeting brought together the 53rd Scientific Meeting of the Italian Statistical Society (SIS 2026) and the 1st Scientific Meeting of the European Statistical Societies (FENStatS 2026) promoted by the Federation of European National Statistical Societies. This volume features the last part of the contributions presented in the Contributed Sessions.The contributions present modern methodological developments and innovative applications in a wide variety of fields and address current challenges in statistical science. The topics covered include, but are not limited to, high-dimensional and multivariate statistics, functional data analysis and complex data structures, Bayesian statistics, time series analysis, dependence and extreme values, statistical learning, machine learning and AI, network science, analysis of directional and compositional data, spatial, spatio-temporal and environmental statistics, biostatistics and the analysis of medical data, social statistics, demography,  economic statistics, as well as survey statistics, official statistics and public policy. Given this variety, the book also demonstrates the importance of statistical science and the responsible use of quantitative methods in addressing societal and environmental challenges related to sustainable development.The Joint Meeting SIS-FENStatS 2026 was the first event of its kind ever organized at the European level. It provided an important forum for dialogue, exchange and collaboration among national and international contributors from academia, national and international institutions, and industry, working across statistics, demography, and applied statistical fields.

This last of four volumes on Statistical Science: From Theory to Applied Research presents peer-reviewed short papers on theoretical and applied statistics presented at the Joint Meeting SIS-FENStatS 2026, held in Rome, Italy, on June 22–25, 2026. The meeting brought together the 53rd Scientific Meeting of the Italian Statistical Society (SIS 2026) and the 1st Scientific Meeting of the European Statistical Societies (FENStatS 2026) promoted by the Federation of European National Statistical Societies. This volume features the last part of the contributions presented in the Contributed Sessions.The contributions present modern methodological developments and innovative applications in a wide variety of fields and address current challenges in statistical science. The topics covered include, but are not limited to, high-dimensional and multivariate statistics, functional data analysis and complex data structures, Bayesian statistics, time series analysis, dependence and extreme values, statistical learning, machine learning and AI, network science, analysis of directional and compositional data, spatial, spatio-temporal and environmental statistics, biostatistics and the analysis of medical data, social statistics, demography,  economic statistics, as well as survey statistics, official statistics and public policy. Given this variety, the book also demonstrates the importance of statistical science and the responsible use of quantitative methods in addressing societal and environmental challenges related to sustainable development.The Joint Meeting SIS-FENStatS 2026 was the first event of its kind ever organized at the European level. It provided an important forum for dialogue, exchange and collaboration among national and international contributors from academia, national and international institutions, and industry, working across statistics, demography, and applied statistical fields.

This second of four volumes on Statistical Science: From Theory to Applied Research presents peer-reviewed short papers on theoretical and applied statistics presented at the Joint Meeting SIS-FENStatS 2026, held in Rome, Italy, on June 22–25, 2026. The meeting brought together the 53rd Scientific Meeting of the Italian Statistical Society (SIS 2026) and the 1st Scientific Meeting of the European Statistical Societies (FENStatS 2026) promoted by the Federation of European National Statistical Societies. This volume features the first part of the contributions presented in the Contributed Sessions.The contributions present modern methodological developments and innovative applications in a wide variety of fields and address current challenges in statistical science. The topics covered include, but are not limited to, high-dimensional and multivariate statistics, functional data analysis and complex data structures, Bayesian statistics, time series analysis, dependence and extreme values, statistical learning, machine learning and AI, network science, analysis of directional and compositional data, spatial, spatio-temporal and environmental statistics, biostatistics and the analysis of medical data, social statistics, demography,  economic statistics, as well as survey statistics, official statistics and public policy. Given this variety, the book also demonstrates the importance of statistical science and the responsible use of quantitative methods in addressing societal and environmental challenges related to sustainable development.The Joint Meeting SIS-FENStatS 2026 was the first event of its kind ever organized at the European level. It provided an important forum for dialogue, exchange and collaboration among national and international contributors from academia, national and international institutions, and industry, working across statistics, demography, and applied statistical fields.

This second of four volumes on Statistical Science: From Theory to Applied Research presents peer-reviewed short papers on theoretical and applied statistics presented at the Joint Meeting SIS-FENStatS 2026, held in Rome, Italy, on June 22–25, 2026. The meeting brought together the 53rd Scientific Meeting of the Italian Statistical Society (SIS 2026) and the 1st Scientific Meeting of the European Statistical Societies (FENStatS 2026) promoted by the Federation of European National Statistical Societies. This volume features the first part of the contributions presented in the Contributed Sessions.The contributions present modern methodological developments and innovative applications in a wide variety of fields and address current challenges in statistical science. The topics covered include, but are not limited to, high-dimensional and multivariate statistics, functional data analysis and complex data structures, Bayesian statistics, time series analysis, dependence and extreme values, statistical learning, machine learning and AI, network science, analysis of directional and compositional data, spatial, spatio-temporal and environmental statistics, biostatistics and the analysis of medical data, social statistics, demography,  economic statistics, as well as survey statistics, official statistics and public policy. Given this variety, the book also demonstrates the importance of statistical science and the responsible use of quantitative methods in addressing societal and environmental challenges related to sustainable development.The Joint Meeting SIS-FENStatS 2026 was the first event of its kind ever organized at the European level. It provided an important forum for dialogue, exchange and collaboration among national and international contributors from academia, national and international institutions, and industry, working across statistics, demography, and applied statistical fields.

This third of four volumes on Statistical Science: From Theory to Applied Research presents peer-reviewed short papers on theoretical and applied statistics presented at the Joint Meeting SIS-FENStatS 2026, held in Rome, Italy, on June 22–25, 2026. The meeting brought together the 53rd Scientific Meeting of the Italian Statistical Society (SIS 2026) and the 1st Scientific Meeting of the European Statistical Societies (FENStatS 2026) promoted by the Federation of European National Statistical Societies. This volume features the second part of the contributions presented in the Contributed Sessions.The contributions present modern methodological developments and innovative applications in a wide variety of fields and address current challenges in statistical science. The topics covered include, but are not limited to, high-dimensional and multivariate statistics, functional data analysis and complex data structures, Bayesian statistics, time series analysis, dependence and extreme values, statistical learning, machine learning and AI, network science, analysis of directional and compositional data, spatial, spatio-temporal and environmental statistics, biostatistics and the analysis of medical data, social statistics, demography,  economic statistics, as well as survey statistics, official statistics and public policy. Given this variety, the book also demonstrates the importance of statistical science and the responsible use of quantitative methods in addressing societal and environmental challenges related to sustainable development.The Joint Meeting SIS-FENStatS 2026 was the first event of its kind ever organized at the European level. It provided an important forum for dialogue, exchange and collaboration among national and international contributors from academia, national and international institutions, and industry, working across statistics, demography, and applied statistical fields.

This third of four volumes on Statistical Science: From Theory to Applied Research presents peer-reviewed short papers on theoretical and applied statistics presented at the Joint Meeting SIS-FENStatS 2026, held in Rome, Italy, on June 22–25, 2026. The meeting brought together the 53rd Scientific Meeting of the Italian Statistical Society (SIS 2026) and the 1st Scientific Meeting of the European Statistical Societies (FENStatS 2026) promoted by the Federation of European National Statistical Societies. This volume features the second part of the contributions presented in the Contributed Sessions.The contributions present modern methodological developments and innovative applications in a wide variety of fields and address current challenges in statistical science. The topics covered include, but are not limited to, high-dimensional and multivariate statistics, functional data analysis and complex data structures, Bayesian statistics, time series analysis, dependence and extreme values, statistical learning, machine learning and AI, network science, analysis of directional and compositional data, spatial, spatio-temporal and environmental statistics, biostatistics and the analysis of medical data, social statistics, demography,  economic statistics, as well as survey statistics, official statistics and public policy. Given this variety, the book also demonstrates the importance of statistical science and the responsible use of quantitative methods in addressing societal and environmental challenges related to sustainable development.The Joint Meeting SIS-FENStatS 2026 was the first event of its kind ever organized at the European level. It provided an important forum for dialogue, exchange and collaboration among national and international contributors from academia, national and international institutions, and industry, working across statistics, demography, and applied statistical fields.

The purpose of this book is to thoroughly prepare the reader for applied research in clustering. Cluster analysis comprises a class of statistical techniques for classifying multivariate data into groups or clusters based on their similar features. Clustering is nowadays widely used in several domains of research, such as social sciences, psychology, and marketing, highlighting its multidisciplinary nature. This book provides an accessible and comprehensive introduction to clustering and offers practical guidelines for applying clustering tools by carefully chosen real-life datasets and extensive data analyses. The procedures addressed in this book include traditional hard clustering methods and up-to-date developments in soft clustering. Attention is paid to practical examples and applications through the open source statistical software R. Commented R code and output for conducting, step by step, complete cluster analyses are available. The book is intended for researchers interested in applying clustering methods. Basic notions on theoretical issues and on R are provided so that professionals as well as novices with little or no background in the subject will benefit from the book.