Advances in Complex Data Modeling and Computational Methods in Statistics

Anna Maria Paganoni (u. a.)

ISBN 10: 3319385372 / ISBN 13: 9783319385372

Published by Springer, 2016

About this Item

Advances in Complex Data Modeling and Computational Methods in Statistics | Anna Maria Paganoni (u. a.) | Taschenbuch | Contributions to Statistics | viii | Englisch | 2016 | Springer | EAN 9783319385372 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Seller Inventory # 103434392

Bibliographic Details

• Title: Advances in Complex Data Modeling and Computational Methods in Statistics
• Publisher: Springer
• Publication Date: 2016
• Language: English
• ISBN 10: 3319385372
• ISBN 13: 9783319385372
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 13D millimeters 235 millimeters width by 155 millimeters height by 13 millimeters depth
• Weight: 341 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

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.