Contributions to Statistics

Complex Data Modeling and Computationally Intensive Statistical Methods

Authors: Mantovan, Pietro, Secchi, Piercesare

  • The book offers a wide variety of statistical methods and is addressed to statisticians working at the forefront of statistical analysis

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  • ISBN 978-88-470-1386-5
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  • ISBN 978-88-470-1385-8
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About this book

The last years have seen the advent and development of many devices able to record and store an always increasing amount of complex and high dimensional data; 3D images generated by medical scanners or satellite remote sensing, DNA microarrays, real time financial data, system control datasets, ....

The analysis of this data poses new challenging problems and requires the development of novel statistical models and computational methods, fueling many fascinating and fast growing research areas of modern statistics. The book offers a wide variety of statistical methods and is addressed to statisticians working at the forefront of statistical analysis.

About the authors

Pietro Mantovan has been Professor of Statistics since 1986 at the University Ca' Foscari of Venezia, Italy, where he has served as coordinator of research units, head of the Departement of Statistics, and Dean of the Faculty of Economics. He has written several articles, monographs and textbooks on classical and Bayesian methods for statistical inference. His recent research interests focus on Bayesian methods for learning and prediction, statistical perturbation models for matrix data, dynamic regression with covariate errors, parallel algorithms for system identification in dynamic models, on line monitoring and forecasting of environmental data, hydrological forecasting uncertainty assessment, and robust inference processes.

Piercesare Secchi is Professor of Statistics at MOX since 2005 and Director of the Department of Mathematics at the Politecnico di Milano. He got a Doctorate in Methodological Statistics from the University of Trento in 1992 and a PhD in Statistics from the University of Minnesota in 1995. He has written several papers on stochastic games and on Bayesian nonparametric predictive inference and bootstrap techniques. His present research interests focus on statistical methods for the exploration, classification and analysis of high dimensional data, like functional data or images generated by medical diagnostic devices or by remote sensing. He also works on models for Bayesian inference, in particular those generated by urn schemes, on response adaptive designs of experiments for clinical trials and on biodata mining. He is PI of different projects in applied statistics and coordinator of the Statistical Unit of the Aneurisk project.

Reviews

From the reviews:

“This volume will be useful for the researchers working in this area. I read a few papers and, all in all, the book seems to have good applications. … All the papers are well structured and consistent in style and presentations. Each paper begins with an abstract and ends with a list of references. … The volume offers a host of computer intensive techniques and applications, and a number of statistical models dealing with complex and high-dimensional data-related problems.” (Technometrics, Vol. 54 (1), February, 2012)


Table of contents (12 chapters)

  • Space-time texture analysis in thermal infrared imaging for classification of Raynaud’s Phenomenon

    Aretusi, Graziano (et al.)

    Pages 1-12

  • Mixed-effects modelling of Kevlar fibre failure times through Bayesian non-parametrics

    Argiento, Raffaele (et al.)

    Pages 13-26

  • Space filling and locally optimal designs for Gaussian Universal Kriging

    Antognini, Alessandro Baldi (et al.)

    Pages 27-39

  • Exploitation, integration and statistical analysis of the Public Health Database and STEMI Archive in the Lombardia region

    Barbieri, Pietro (et al.)

    Pages 41-55

  • Bootstrap algorithms for variance estimation in πPS sampling

    Barbiero, Alessandro (et al.)

    Pages 57-69

Buy this book

eBook $84.99
price for USA (gross)
  • ISBN 978-88-470-1386-5
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $109.00
price for USA
  • ISBN 978-88-470-1385-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Complex Data Modeling and Computationally Intensive Statistical Methods
Authors
Series Title
Contributions to Statistics
Copyright
2010
Publisher
Springer-Verlag Mailand
Copyright Holder
Springer-Verlag Milan
eBook ISBN
978-88-470-1386-5
DOI
10.1007/978-88-470-1386-5
Hardcover ISBN
978-88-470-1385-8
Series ISSN
1431-1968
Edition Number
1
Number of Pages
X, 164
Topics