Studies in Theoretical and Applied Statistics

This book includes a wide selection of papers presented at the 50th Scientific Meeting of the Italian Statistical Society (SIS2021), held virtually on 21-125 June 2021. It covers a wide variety of subjects ranging from methodological and theoretical contributions to applied works and case studies, giving an excellent overview of the interests of the Italian statisticians and their international collaborations. Intended for researchers interested in theoretical and empirical issues, this volume provides interesting starting points for further research.

Auteur

Nicola Salvati is Associate Professor in Statistics in the Department of Economics and Management, University of Pisa, Italy. He is Associate Editor for the Biometrical Journal, the Journal of the Royal Statistical Society (Series A) and Statistical Methods & Applications. His research is focused on small area estimation, and particularly its use to estimate poverty measures when based on M-quantile and latent variable models. His research interests also include survey sampling, model-assisted and design-based inference, robust regression and spatial statistics. His most recent area of research involves development of new statistical methods based on latent variable models for estimating parameters from non-deterministically linked data.

Cira Perna is full professor of Statistics at the Department of Economics and Statistics of the University of Salerno (Italy). Her research work mainly focuses on non-linear time series, artificial neural network models and resampling techniques. On these topics, she has published numerous papers in national and international journals. She has participated in several research projects, both at national and international level and she has been a member of several scientific committees of national and international conferences.

Stefano Marchetti graduated in Statistical Sciences at the University of Pisa. He got a PhD in Applied Statistics at the University of Florence in 2009. He is Associate Professor in Statistics at the Department of Economics and Management of the University of Pisa. He teaches Statistics in graduate, master and PhD courses of the University of Pisa. His main research interests include Small Area Estimation, M-quantile models, Bootstrap, Poverty estimation and mapping.

Ray Chambers is Honorary Professorial Fellow at the National Institute for Applied Statistics Research Australia, University of Wollongong, Australia. He is an elected member of the International Statistical Institute and a Fellow of the American Statistical Association. He was co-Editor in Chief of the International Statistical Review 2015-2019 and has been an Associate Editor for the Journal of Official Statistics, Survey Methodology, the Journal of the Royal Statistical Society (Series A and B) and the Annals of Statistics. He was President of the International Association of Survey Statisticians, 2011-2013 and International Representative on the Board of the American Statistical Association, 2011-2014. His research is focused on robust model-based methods for inference from complex data, particularly where this complexity arises through integration of data from multiple sources. With Chris Skinner, he jointly edited Analysis of Survey Data, Wiley, 2003. More recently, he co-authored Maximum Likelihood Estimation for Sample Surveys, CRC Press, 2012, with David Steel, Alan Welsh and Suojin Wang, and An Introduction to Model-Based Survey Sampling with Applications, Oxford University Press, 2012, with Robert Clark.

Ray Chambers is Honorary Professorial Fellow at the National Institute for Applied Statistics Research Australia, University of Wollongong, Australia. He is an elected member of the International Statistical Institute and a Fellow of the American Statistical Association. He was co-Editor in Chief of the International Statistical Review 2015-2019 and has been an Associate Editor for the Journal of Official Statistics, Survey Methodology, the Journal of the Royal Statistical Society (Series A and B) and the Annals of Statistics. He was President of the International Association of Survey Statisticians, 2011-2013 and International Representative on the Board of the American Statistical Association, 2011-2014. His research is focused on robust model-based methods for inference from complex data, particularly where this complexity arises through integration of data from multiple sources. With Chris Skinner, he jointly edited Analysis of Survey Data, Wiley, 2003. More recently, he co-authored Maximum Likelihood Estimation for Sample Surveys, CRC Press, 2012, with David Steel, Alan Welsh and Suojin Wang, and An Introduction to Model-Based Survey Sampling with Applications, Oxford University Press, 2012, with Robert Clark.