Astrostatistics and Data Mining

  • Luis Manuel Sarro
  • Laurent Eyer
  • William O'Mullane
  • Joris De Ridder

Part of the Springer Series in Astrostatistics book series (SSIA, volume 2)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Invited Talks

    1. Front Matter
      Pages 1-1
    2. Massimo Brescia, Stefano Cavuoti, George S. Djorgovski, Ciro Donalek, Giuseppe Longo, Maurizio Paolillo
      Pages 31-45
    3. Matthew J. Graham
      Pages 47-59
  3. Contributed Talks

    1. Front Matter
      Pages 61-61
    2. Y. Ascasibar, J. Sánchez Almeida
      Pages 63-69
    3. Miguel Cárdenas-Montes, Mercedes Mollá, Miguel A. Vega-Rodríguez, Juan José Rodríguez-Vázquez, Antonio Gómez-Iglesias
      Pages 81-88
    4. Pedro David, Jerome Berthier, Daniel Hestroffer
      Pages 97-105
    5. Pilar de Teodoro, Alexander Hutton, Benoit Frezouls, Alain Montmory, Jordi Portell, Rosario Messineo et al.
      Pages 107-115
    6. P. Dubath, I. Lecoeur-Taïbi, L. Rimoldini, M. Süveges, J. Blomme, M. López et al.
      Pages 117-125
    7. Diego Fustes, Diego Ordóñez, Carlos Dafonte, Minia Manteiga, Bernardino Arcay
      Pages 127-131
    8. Berry Holl, Lennart Lindegren, David Hobbs
      Pages 133-141
    9. Francisco-Shu Kitaura
      Pages 143-154
    10. Chao Liu, Coryn A. L. Bailer-Jones
      Pages 155-162
    11. James P. Long, Joshua S. Bloom, Noureddine El Karoui, John Rice, Joseph W. Richards
      Pages 163-171

About this book

Introduction

This volume provides an overview of the field of Astrostatistics understood as the sub-discipline dedicated to the statistical analysis of astronomical data. It presents examples of the application of the various methodologies now available to current open issues in astronomical research. The technical aspects related to the scientific analysis of the upcoming petabyte-scale databases are emphasized given the importance that scalable Knowledge Discovery techniques will have for the full exploitation of these databases.

Based on the 2011 Astrostatistics and Data Mining in Large Astronomical Databases conference and school, this volume gathers examples of the work by leading authors in the areas of Astrophysics and Statistics, including a significant contribution from the various teams that prepared for the processing and analysis of the Gaia data.

Keywords

Astrostatistics Data Mining Statistical Astronomy

Editors and affiliations

  • Luis Manuel Sarro
    • 1
  • Laurent Eyer
    • 2
  • William O'Mullane
    • 3
  • Joris De Ridder
    • 4
  1. 1., Department of StatisticsUniversidad Nacional EducacionMadridSpain
  2. 2., Observatoire de GenèveUniversité de GenèveSauvernySwitzerland
  3. 3.European Space Astronomy CentreMadridSpain
  4. 4., Instituut voor SterrenkundeKatholieke Universiteit LeuvenLeuvenBelgium

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-3323-1
  • Copyright Information Springer Science+Business Media New York 2012
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4614-3322-4
  • Online ISBN 978-1-4614-3323-1
  • About this book