Advances in complex data modeling an...
Paganoni, Anna Maria.

 

  • Advances in complex data modeling and computational methods in statistics[electronic resource] /
  • Record Type: Language materials, printed : Monograph/item
    [NT 15000414]: 519.5
    Title/Author: Advances in complex data modeling and computational methods in statistics/ edited by Anna Maria Paganoni, Piercesare Secchi.
    other author: Paganoni, Anna Maria.
    Published: Cham : : Springer International Publishing :, 2015.
    Description: viii, 209 p. : : ill. (some col.), digital ;; 24 cm.
    Contained By: Springer eBooks
    Subject: Mathematical statistics - Data processing.
    Subject: Statistics.
    Subject: Statistical Theory and Methods.
    Subject: Applications of Mathematics.
    Subject: Biostatistics.
    Subject: Complexity.
    Subject: Software Engineering/Programming and Operating Systems.
    ISBN: 9783319111490 (electronic bk.)
    ISBN: 9783319111483 (paper)
    [NT 15000229]: 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.
    Online resource: http://dx.doi.org/10.1007/978-3-319-11149-0
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