This book brings together selected peer-reviewed contributions from various research fields in statistics, and highlights the diverse approaches and analyses related to real-life phenomena.
Major topics covered in this volume include, but are not limited to, bayesian inference, likelihood approach, pseudo-likelihoods, regression, time series, and data analysis as well as applications in the life and social sciences.
The software packages used in the papers are made available by the authors.
This book is a result of the 47th Scientific Meeting of the Italian Statistical Society, held at the University of Cagliari, Italy, in 2014.
About the Author
The three editors are researchers well known to national and international statistical community. In addition, each of them has a large scientific production and the results of their research are published in numerous journals well classified.
Table of Contents
Introducing Prior Information into the Forward Search for Regression.- A Finite Mixture Latent Trajectory Model for Hirings and Separations in the Labor Market.- Outliers in Time Series - An Empirical Likelihood Approach.- Advanced Methods to Design Samples for Land Use/Land Cover Surveys.- Heteroscedasticity, Multiple Populations and Outliers in Trade Data.- How to Marry Robustness and Applied Statistics.- Logistic Quantile Regression to Model Cognitive Impairment in Sardinian Cancer Patients.- Bounding the Probability of Causation in Mediation Analysis.- Analysis of Collaboration Structures though Time - The Case of Technological Districts.- Bayesian Spatio-temporal Modeling of Urban Air Pollution Dynamics.- Clustering Functional Data on Convex Function Spaces.- The Impact of Demographic Change on Sustainability of Emergency Departments.- Bell Shaped Fuzzy Numbers Associated With the Normal Curve.- Improving Co-authorship Network Structures by Combining Heterogeneous Data Sources.- Statistical Issues in Bayesian Meta-Analysis.- Statistical Evaluation of Forensic DNA Mixtures from Multiple Traces.- A Note on Semivariogram.- Geographically Weighted Regression Analysis of Cardiovascular Diseases - Evidence From Canada Health Data.- Pseudo-Likelihoods for Bayesian Inference.