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The Contribution of Young Researchers to Bayesian Statistics
The first Bayesian Young Statisticians Meeting, BAYSM 2013, has provided a unique opportunity for young researchers, M.S. students, Ph.D. students, and post-docs dealing with Bayesian statistics to connect with the Bayesian community at large, exchange ideas, and network with scholars working in their field. The Workshop, which took place June 5th and 6th 2013 at CNR-IMATI, Milan, has promoted further research in all the fields where Bayesian statistics may be employed under the guidance of renowned plenary lecturers and senior discussants. A selection of the contributions to the meeting and the summary of one of the plenary lectures compose this volume.
Contributions in infinite-dimensional statistics and related topics
The interest towards Functional and Operatorial Statistics, and, more in general, towards infinite-dimensional statistics has dramatically increased in the statistical community and in many other applied scientific areas where people faces functional data. This volume collects the works selected and presented at the Third Edition of the International Workshop on Functional and Operatorial Statistics held in Stresa, Italy, from the 19th to the 21st of June 2014 (IWFOS’2014). The meeting represents an opportunity of bringing together leading researchers active on these topics both for what concerns theoretical aspects and a wide range of applications in various fields. To promote collaborations with other important strictly related areas of infinite-dimensional Statistics, such as High Dimensional Statistics and Model Selection Procedures, this book hosts works in the latter research subjects too.
Cladag 2017 Book of Short Papers
This book is the collection of the Abstract / Short Papers submitted by the authors of the International Conference of The CLAssification and Data Analysis Group (CLADAG) of the Italian Statistical Society (SIS), held in Milan (Italy) on September 13-15, 2017.
Complex Models and Computational Methods in Statistics
The use of computational methods in statistics to face complex problems and highly dimensional data, as well as the widespread availability of computer technology, is no news. The range of applications, instead, is unprecedented. As often occurs, new and complex data types require new strategies, demanding for the development of novel statistical methods and suggesting stimulating mathematical problems. This book is addressed to researchers working at the forefront of the statistical analysis of complex systems and using computationally intensive statistical methods.
Advances in Complex Data Modeling and Computational Methods in Statistics
The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.
Statistical Models for Data Analysis
The papers in this book cover issues related to the development of novel statistical models for the analysis of data. They offer solutions for relevant problems in statistical data analysis and contain the explicit derivation of the proposed models as well as their implementation. The book assembles the selected and refereed proceedings of the biannual conference of the Italian Classification and Data Analysis Group (CLADAG), a section of the Italian Statistical Society.
New Diagnostic, Therapeutic and Organizational Strategies for Acute Coronary Syndromes Patients
This book collects several contributions, written both by statisticians and medical doctors, which focus on the identification of new diagnostic, therapeutic and organizational strategies in order to improve the occurrence of clinical outcomes for Acute Coronary Syndromes (ACS) patients. The work is structured in two different parts: the first one is focused on cooperative project mainly on statistical analysis of large clinical and administrative databases; the second one faces the development of innovative diagnostic techniques, with specific reference to genetic and proteomic, and the evolution of new imaging techniques for the early identification of patients at major risk of thrombotic, arrhythmic complications and at risk of poor revascularization.
Advances in Theoretical and Applied Statistics
This volume includes contributions selected after a double blind review process and presented as a preliminary version at the 45th Meeting of the Italian Statistical Society. The papers provide significant and innovative original contributions and cover a broad range of topics including: statistical theory; methods for time series and spatial data; statistical modeling and data analysis; survey methodology and official statistics; analysis of social, demographic and health data; and economic statistics and econometrics.
Functional and High-Dimensional Statistics and Related Fields
This book presents the latest research on the statistical analysis of functional, high-dimensional and other complex data, addressing methodological and computational aspects, as well as real-world applications. It covers topics like classification, confidence bands, density estimation, depth, diagnostic tests, dimension reduction, estimation on manifolds, high- and infinite-dimensional statistics, inference on functional data, networks, operatorial statistics, prediction, regression, robustness, sequential learning, small-ball probability, smoothing, spatial data, testing, and topological object data analysis, and includes applications in automobile engineering, criminology, drawing recogni...
