High-quality and Timely Statistics: New Methods and Applications - Couverture rigide

Couverture rigide

ISBN 10 : 3031636295 ISBN 13 : 9783031636295

Editeur : Springer International Publishing AG, 2024

Synopsis

This book addresses a wide range of recent methodological aspects, applications and best practices of statistics production. It comprises a selection of peer-reviewed contributions of methodological and applied interest presented at the 4th Conference of European Statistics Stakeholders, CESS 2022, held in Rome, Italy, on October 20-21, 2022. The first part discusses statistical methods with applications to environmental risk assessment, sentinels data, surveillance systems during the Covid-19 pandemic, healthcare risk management, the analysis of regional or structural changes of scale, household distributional accounts, regional rental prices on municipalities, the network topology of the Euro area interbank market, tourism statistics and big data, statistical literacy, and Sustainable Development Goal composite indicators for EU countries. The second part focuses on statistical methodologies for complex data analysis, namely the optimal number of clusters to rank a model-based index, clustering methods for asymmetric data using spectral approaches, a family of parsimonious matrix-variate mixture models for heavy-tailed data, the importance of robust second-stage regressions for financial data, and on perturbation methods.

In view of the overarching theme “The European Data Ecosystem for the Statistical Information of the Digital Age” and the importance of statistical data for monitoring the progress of the United Nations’ Sustainable Development Goals, the CESS 2022 meeting provided a forum for discussion on methodologies, results, challenges and best practices among methodologists, producers, and users of European Statistics from academia, the national statistical offices and the institutions of the European Union.

Chapter Estimating regional rental prices on LAU 2 municipalities in North Rhine-Westphalia is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

A propos du livre

À propos de l?auteur

Marco Mingione is an Assistant Professor at the Department of Political Sciences, Roma Tre University, Italy. His fields of interest are Bayesian hierarchical modeling, hidden semi-Markov models, official statistics and R programming. He is also an elected member of the board of Y-SIS, the Young group of the Italian Statistical Society.

Maurizio Vichi is a Professor of Statistics and Chair of the Department of Statistical Sciences at Sapienza University of Rome, Italy. 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 a member of the European Statistical Advisory Committee of the European Union and the Coordinating Editor of the international journal Advances in Data Analysis and Classification. He has authored more than 150 papers, mainly published in peer-reviewed international statistics journals.

Giorgia Zaccaria is a Postdoctoral Research Fellow at the Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Italy. Her fields of interest are hierarchical and latent variable models, dimensionality reduction, model-based clustering, ultrametric models, robust statistics, and composite indicators. She is also an elected member of the board of Y-SIS, the Young group of the Italian Statistical Society.

Détails de l'édition

• Éditeur: Springer International Publishing AG
• Date d'édition: 2024
• Langue: anglais
• ISBN 10: 3031636295
• ISBN 13: 9783031636295
• Reliure: Relié
• Nombre de pages: 281
• Éditeur: Mingione Marco, Vichi Maurizio, Zaccaria Giorgia
• Coordonnées du fabricant: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Allemagne