Advances in Complex Data Modeling and Computational Methods in Statistics [electronic resource] /
Paganoni, Anna Maria.editor.
Secchi, Piercesare.editor.
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.
Description based upon print version of record.
Includes bibliographical references.
1 Antonino Abbruzzo, Angelo M. Mineo: Inferring networks from high-dimensional data with mixed variables -- 2 Federico Andreis, Fulvia Mecatti: Rounding Non-integer Weights in Bootstrapping Non-iid Samples: actual problem or harmless practice? -- 3 Marika Arena, Giovanni Azzone, Antonio Conte, Piercesare Secchi, Simone Vantini: Measuring downsize reputational risk in the Oil & Gas industry -- 4 Laura Azzimonti, Marzia A. Cremona, Andrea Ghiglietti, Francesca Ieva, Alessandra Menafoglio, Alessia Pini, Paolo Zanini: BARCAMP Technology Foresight and Statistics for the Future -- 5 Francesca Chiaromonte, Kateryna D. Makova: Using statistics to shed light on the dynamics of the human genome: A review -- 6 Nader Ebrahimi, Ehsan S. Soofi and Refik Soyer: Information Theory and Bayesian Reliability Analysis: Recent Advances -- 7 Stephan F. Huckemann: (Semi-) Intrinsic Statistical Analysis on non-Euclidean Spaces -- 8 John T. Kent: An investigation of projective shape space -- 9 Fabio Manfredini, Paola Pucci, Piercesare Secchi, Paolo Tagliolato, Simone Vantini, Valeria Vitelli: Treelet Decomposition of Mobile Phone Data for Deriving City Usage and Mobility Pattern in the Milan Urban Region -- 10 Cristina Mazzali, Mauro Maistriello, Francesca Ieva, Pietro Barbieri: Methodological issues in the use of administrative databases to study heart failure -- 11 Andrea Mercatant: Bayesian inference for randomized experiments with noncompliance and nonignorable missing data -- 12 Antonio Pulcini, Brunero Liseo: Approximate Bayesian Quantile Regression for Panel Data -- 13 Laura M. Sangalli: Estimating surfaces and spatial fields via regression models with differential regularization.  .
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.
Statistics .
Applied mathematics.
Engineering mathematics.
Biostatistics.
Computational complexity.
Software engineering.
Statistical Theory and Methods.
Applications of Mathematics.
Biostatistics.
Complexity.
Software Engineering/Programming and Operating Systems.