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Complex Models and Computational Methods in Statistics

  • Book
  • © 2013

Overview

Editors:
  1. Matteo Grigoletto

    1. , Statistical Sciences, University of Padua, Padua, Italy, Padova, Italy

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  2. Francesco Lisi

    1. , Statistical Sciences, University of Padua, Padua, Italy, Padova, Italy

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    You can also search for this editor in PubMed   Google Scholar

  3. Sonia Petrone

    1. , Dept of Decision Sciences, Bocconi University, Milano, Italy

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    You can also search for this editor in PubMed   Google Scholar

  • The volume offers an updated overview of statistical methods for high-dimensional problems
  • It includes a wide range of statistical applications
  • It is addressed to the statistician working at the forefront of statistical analysis
  • Includes supplementary material: sn.pub/extras

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

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Table of contents (17 chapters)

  1. Front Matter

    Pages i-viii
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  2. A New Unsupervised Classification Technique Through Nonlinear Non Parametric Mixed-Effects Models

    • Laura Azzimonti, Francesca Ieva, Anna Maria Paganoni
    Pages 1-11

  3. Estimation Approaches for the Apparent Diffusion Coefficient in Rice-Distributed MR Signals

    • Stefano Baraldo, Francesca Ieva, Luca Mainardi, Anna Maria Paganoni
    Pages 13-26

  4. Longitudinal Patterns of Financial Product Ownership: A Latent Growth Mixture Approach

    • Francesca Bassi, José G. Dias
    Pages 27-36

  5. Computationally Efficient Inference Procedures for Vast Dimensional Realized Covariance Models

    • Luc Bauwens, Giuseppe Storti
    Pages 37-49

  6. A GPU Software Library for Likelihood-Based Inference of Environmental Models with Large Datasets

    • Michela Cameletti, Francesco Finazzi
    Pages 51-62

  7. Theoretical Regression Trees: A Tool for Multiple Structural-Change Models Analysis

    • Carmela Cappelli, Francesca Di Iorio
    Pages 63-76

  8. Some Contributions to the Theory of Conditional Gibbs Partitions

    • Annalisa Cerquetti
    Pages 77-89

  9. Estimation of Traffic Matrices for LRD Traffic

    • Pier Luigi Conti, Livia De Giovanni, Maurizio Naldi
    Pages 91-107

  10. A Newton’s Method for Benchmarking Time Series

    • Tommaso Di Fonzo, Marco Marini
    Pages 109-121

  11. Spatial Smoothing for Data Distributed over Non-planar Domains

    • Bree Ettinger, Tiziano Passerini, Simona Perotto, Laura M. Sangalli
    Pages 123-135

  12. Volatility Swings in the US Financial Markets

    • Giampiero M. Gallo, Edoardo Otranto
    Pages 137-148

  13. Semicontinuous Regression Models with Skew Distributions

    • Anna Gottard, Elena Stanghellini, Rosa Capobianco
    Pages 149-160

  14. Classification of Multivariate Linear-Circular Data with Nonignorable Missing Values

    • Francesco Lagona, Marco Picone
    Pages 161-173

  15. Multidimensional Connected Set Detection in Clustering Based on Nonparametric Density Estimation

    • Giovanna Menardi
    Pages 175-186

  16. Using Integrated Nested Laplace Approximations for Modelling Spatial Healthcare Utilization

    • Monica Musio, Erik-A. Sauleau, Valentina Mameli
    Pages 187-201

  17. Supply Function Prediction in Electricity Auctions

    • Matteo Pelagatti
    Pages 203-213

  18. A Hierarchical Bayesian Model for RNA-Seq Data

    • Davide Risso, Gabriele Sales, Chiara Romualdi, Monica Chiogna
    Pages 215-227
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Keywords

About this book

The use of computational methods in statistics to face complex problems and highly dimensional data, as well as the widespread availability of computer technology, is no news. The range of applications, instead, is unprecedented.

As often occurs, new and complex data types require new strategies, demanding for the development of novel statistical methods and suggesting stimulating mathematical problems.

This book is addressed to researchers working at the forefront of the statistical analysis of complex systems and using computationally intensive statistical methods.

Reviews

“Complex Models and Computational Methods in Statistics has a good collection of research papers on useful and interesting topics about complex and high-dimensional data. Researchers and professionals looking to learn more in this field of study could benefit from papers published in this volume. The content in most of these selected papers proved to be an enjoyable read.” (Technometrics, Vol. 56 (3), August, 2014)

Editors and Affiliations

  • , Statistical Sciences, University of Padua, Padua, Italy, Padova, Italy

    Matteo Grigoletto, Francesco Lisi

  • , Dept of Decision Sciences, Bocconi University, Milano, Italy

    Sonia Petrone

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