Advances in Complex Data Modeling and Computational Methods in Statistics

This document was uploaded by one of our users. The uploader already confirmed that they had the permission to publish it. If you are author/publisher or own the copyright of this documents, please report to us by using this DMCA report form.

Simply click on the Download Book button.

Yes, Book downloads on Ebookily are 100% Free.

Sometimes the book is free on Amazon As well, so go ahead and hit "Search on Amazon"

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.

Author(s): Anna Maria Paganoni, Piercesare Secchi (eds.)
Series: Contributions to Statistics
Edition: 1
Publisher: Springer International Publishing
Year: 2015

Language: English
Pages: 209
Tags: Statistical Theory and Methods; Applications of Mathematics; Biostatistics; Complexity; Software Engineering/Programming and Operating Systems

Front Matter....Pages i-viii
Inferring Networks from High-Dimensional Data with Mixed Variables....Pages 1-15
Rounding Non-integer Weights in Bootstrapping Non-iid Samples: Actual Problem or Harmless Practice?....Pages 17-35
Measuring Downsize Reputational Risk in the Oil & Gas Industry....Pages 37-51
BarCamp: Technology Foresight and Statistics for the Future....Pages 53-67
Using Statistics to Shed Light on the Dynamics of the Human Genome: A Review....Pages 69-85
Information Theory and Bayesian Reliability Analysis: Recent Advances....Pages 87-102
(Semi-)Intrinsic Statistical Analysis on Non-Euclidean Spaces....Pages 103-118
An Investigation of Projective Shape Space....Pages 119-131
Treelet Decomposition of Mobile Phone Data for Deriving City Usage and Mobility Pattern in the Milan Urban Region....Pages 133-147
Methodological Issues in the Use of Administrative Databases to Study Heart Failure....Pages 149-160
Bayesian Inference for Randomized Experiments with Noncompliance and Nonignorable Missing Data....Pages 161-172
Approximate Bayesian Quantile Regression for Panel Data....Pages 173-189
Estimating Surfaces and Spatial Fields via Regression Models with Differential Regularization....Pages 191-209