Advances in Complex Data Modeling and Computational Methods in Statistics

  • Anna Maria Paganoni
  • Piercesare Secchi

Part of the Contributions to Statistics book series (CONTRIB.STAT.)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Antonino Abbruzzo, Angelo M. Mineo
    Pages 1-15
  3. Marika Arena, Giovanni Azzone, Antonio Conte, Piercesare Secchi, Simone Vantini
    Pages 37-51
  4. Laura Azzimonti, Marzia A. Cremona, Andrea Ghiglietti, Francesca Ieva, Alessandra Menafoglio, Alessia Pini et al.
    Pages 53-67
  5. Francesca Chiaromonte, Kateryna D. Makova
    Pages 69-85
  6. Nader Ebrahimi, Ehsan S. Soofi, Refik Soyer
    Pages 87-102
  7. John T. Kent
    Pages 119-131
  8. Fabio Manfredini, Paola Pucci, Piercesare Secchi, Paolo Tagliolato, Simone Vantini, Valeria Vitelli
    Pages 133-147
  9. Cristina Mazzali, Mauro Maistriello, Francesca Ieva, Pietro Barbieri
    Pages 149-160
  10. Antonio Pulcini, Brunero Liseo
    Pages 173-189

About this book


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.


Biodata mining Classification and prediction of high dimensional data Complex data surveys Computational methods for statistics Statistical methods for industry and technology

Editors and affiliations

  • Anna Maria Paganoni
    • 1
  • Piercesare Secchi
    • 2
  1. 1.Dipartimento di MatematicaPolitecnico di MilanoMilanoItaly
  2. 2.Dipartimento di MatematicaPolitecnico di MilanoMilanoItaly

Bibliographic information