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Advances in Complex Data Modeling and Computational Methods in Statistics

Anna Maria Paganoni, Piercesare Secchi (Herausgeber)

Buch | Hardcover

VIII, 209 Seiten

2014
Springer International Publishing (Verlag)
978-3-319-11148-3 (ISBN)

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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.

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.

Erscheint lt. Verlag	18.11.2014
Reihe/Serie	Contributions to Statistics
Zusatzinfo	VIII, 209 p. 41 illus., 27 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	470 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Statistik
Themenwelt	Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
Schlagworte	biodata mining • Classification and prediction of high dimensional • Classification and prediction of high dimensional data • complex data surveys • Complexity • computational methods for statistics • statistical methods for industry and technology
ISBN-10	3-319-11148-5 / 3319111485
ISBN-13	978-3-319-11148-3 / 9783319111483
Zustand	Neuware