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 development...
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Corporate Author: | |
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Other Authors: | , |
Format: | eBook |
Language: | English |
Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2015.
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Series: | Contributions to Statistics,
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Subjects: | |
Online Access: | Click here to view the full text content |
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Summary: | 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. |
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Physical Description: | 1 online resource (viii, 209 pages) 41 illustrations, 27 illustrations in color |
ISBN: | 9783319111490 |
ISSN: | 1431-1968 |