Advances in Complex Data Modeling and Computational Methods in Statistics

1. Front Matter

   Pages i-viii

   PDF

2. Inferring Networks from High-Dimensional Data with Mixed Variables

   • Antonino Abbruzzo, Angelo M. Mineo

   Pages 1-15

3. Rounding Non-integer Weights in Bootstrapping Non-iid Samples: Actual Problem or Harmless Practice?

   • Federico Andreis, Fulvia Mecatti

   Pages 17-35

4. Measuring Downsize Reputational Risk in the Oil & Gas Industry

   • Marika Arena, Giovanni Azzone, Antonio Conte, Piercesare Secchi, Simone Vantini

   Pages 37-51

5. BarCamp: Technology Foresight and Statistics for the Future

   • Laura Azzimonti, Marzia A. Cremona, Andrea Ghiglietti, Francesca Ieva, Alessandra Menafoglio, Alessia Pini et al.

   Pages 53-67

6. Using Statistics to Shed Light on the Dynamics of the Human Genome: A Review

   • Francesca Chiaromonte, Kateryna D. Makova

   Pages 69-85

7. Information Theory and Bayesian Reliability Analysis: Recent Advances

   • Nader Ebrahimi, Ehsan S. Soofi, Refik Soyer

   Pages 87-102

8. (Semi-)Intrinsic Statistical Analysis on Non-Euclidean Spaces

   • Stephan F. Huckemann

   Pages 103-118

9. An Investigation of Projective Shape Space

   • John T. Kent

   Pages 119-131

10. Treelet Decomposition of Mobile Phone Data for Deriving City Usage and Mobility Pattern in the Milan Urban Region

    • Fabio Manfredini, Paola Pucci, Piercesare Secchi, Paolo Tagliolato, Simone Vantini, Valeria Vitelli

    Pages 133-147

11. Methodological Issues in the Use of Administrative Databases to Study Heart Failure

    • Cristina Mazzali, Mauro Maistriello, Francesca Ieva, Pietro Barbieri

    Pages 149-160

12. Bayesian Inference for Randomized Experiments with Noncompliance and Nonignorable Missing Data

    • Andrea Mercatanti

    Pages 161-172

13. Approximate Bayesian Quantile Regression for Panel Data

    • Antonio Pulcini, Brunero Liseo

    Pages 173-189

14. Estimating Surfaces and Spatial Fields via Regression Models with Differential Regularization

    • Laura M. Sangalli

    Pages 191-209

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
• complexity

• Dipartimento di Matematica, Politecnico di Milano, Milano, Italy

  Anna Maria Paganoni, Piercesare Secchi

Policies and ethics