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Astrostatistics and Data Mining

  • Book
  • © 2012

Overview

Editors:
  1. Luis Manuel Sarro

    1. , Department of Statistics, Universidad Nacional Educacion, Madrid, Spain

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  2. Laurent Eyer

    1. , Observatoire de Genève, Université de Genève, Sauverny, Switzerland

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  3. William O'Mullane

    1. European Space Astronomy Centre, Madrid, Spain

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  4. Joris De Ridder

    1. , Instituut voor Sterrenkunde, Katholieke Universiteit Leuven, Leuven, Belgium

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  • Provides a concise introduction to data mining and data analysis of astronomical data and astroinformatics in the context of many recent discoveries
  • Details various traditional and non-traditional methodologies for analyzing and interpreting large scale data sets in this field?
  • 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

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

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Table of contents (28 chapters)

  1. Front Matter

    Pages i-xi
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  2. Invited Talks

    1. Front Matter

      Pages 1-1
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    2. Recent Advances in Cosmological Bayesian Model Comparison

      • Roberto Trotta
      Pages 3-15

    3. Science from Gaia: How to Deal with a Complex Billion-Source Catalogue and Data Archive

      • Anthony G. A. Brown
      Pages 17-29

    4. Extracting Knowledge from Massive Astronomical Data Sets

      • Massimo Brescia, Stefano Cavuoti, George S. Djorgovski, Ciro Donalek, Giuseppe Longo, Maurizio Paolillo
      Pages 31-45

    5. The Art of Data Science

      • Matthew J. Graham
      Pages 47-59

  3. Contributed Talks

    1. Front Matter

      Pages 61-61
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    2. The Distribution of Galaxies in Spectral Space

      • Y. Ascasibar, J. Sánchez Almeida
      Pages 63-69

    3. Utilizing Astroinformatics to Maximize the Science Return of the Next Generation Virgo Cluster Survey

      • Nicholas M. Ball
      Pages 71-79

    4. Adjustment of Observational Data to Specific Functional Forms Using a Particle Swarm Algorithm and Differential Evolution: Rotational Curves of a Spiral Galaxy as Case Study

      • Miguel Cárdenas-Montes, Mercedes Mollá, Miguel A. Vega-Rodríguez, Juan José Rodríguez-Vázquez, Antonio Gómez-Iglesias
      Pages 81-88

    5. Probabilistic Description of Stellar Ensembles

      • Miguel Cerviño
      Pages 89-96

    6. Solar System Parameters from the Gaia Small Solar System Object Data

      • Pedro David, Jerome Berthier, Daniel Hestroffer
      Pages 97-105

    7. Data Management at Gaia Data Processing Centers

      • Pilar de Teodoro, Alexander Hutton, Benoit Frezouls, Alain Montmory, Jordi Portell, Rosario Messineo et al.
      Pages 107-115

    8. Hipparcos Variable Star Detection and Classification Efficiency

      • P. Dubath, I. Lecoeur-Taïbi, L. Rimoldini, M. Süveges, J. Blomme, M. López et al.
      Pages 117-125

    9. Distributed Genetic Algorithm for Feature Selection in Gaia RVS Spectra: Application to ANN Parameterization

      • Diego Fustes, Diego Ordóñez, Carlos Dafonte, Minia Manteiga, Bernardino Arcay
      Pages 127-131

    10. Efficient Calculation of Covariances for Astrometric Data in the Gaia Catalogue

      • Berry Holl, Lennart Lindegren, David Hobbs
      Pages 133-141

    11. Bayesian Analysis of Cosmic Structures

      • Francisco-Shu Kitaura
      Pages 143-154

    12. Generalized Stellar Parametrizer with Gaia Photometry Data

      • Chao Liu, Coryn A. L. Bailer-Jones
      Pages 155-162

    13. Classification of Poorly Time Sampled Light Curves of Periodic Variable Stars

      • James P. Long, Joshua S. Bloom, Noureddine El Karoui, John Rice, Joseph W. Richards
      Pages 163-171

    14. Handling Imbalanced Data Sets in Multistage Classification

      • M. López
      Pages 173-179
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Keywords

About this book

​​​​​ ​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.  

Reviews

From the book reviews:

“This book is the result of a 2011 Workshop on Astrostatistics and Data Mining, held on the island of in La Palma. … The book provides a convenient description of many new and planned datasets, with relatively succinct statistical analyses, many of which adopt a Bayesian framework. I believe the book will be most appreciated by astronomers and applied statisticians and note that the four editors include a statistician and several astronomers.” (Thomas Burr, Technometrics, Vol. 55 (4), November, 2013)

Editors and Affiliations

  • , Department of Statistics, Universidad Nacional Educacion, Madrid, Spain

    Luis Manuel Sarro

  • , Observatoire de Genève, Université de Genève, Sauverny, Switzerland

    Laurent Eyer

  • European Space Astronomy Centre, Madrid, Spain

    William O'Mullane

  • , Instituut voor Sterrenkunde, Katholieke Universiteit Leuven, Leuven, Belgium

    Joris De Ridder

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