Statistical Challenges in Modern Astronomy V

  • Eric D. Feigelson
  • G. Jogesh Babu

Part of the Lecture Notes in Statistics book series (LNS, volume 902)

Also part of the Lecture Notes in Statistics - Proceedings book sub series (LNSP, volume 902)

Table of contents

  1. Front Matter
    Pages i-xxiii
  2. Statistics in Cosmology

  3. Bayesian Analysis Across Astronomy

    1. Front Matter
      Pages 99-99
    2. David A. van Dyk
      Pages 141-146
    3. Brandon C. Kelly
      Pages 147-162
    4. Alexander W. Blocker, Pavlos Protopapas
      Pages 177-187
    5. Brendon J. Brewer
      Pages 189-195
    6. Fabrizia Guglielmetti, Rainer Fischer, Volker Dose
      Pages 197-202
    7. Vinay Kashyap
      Pages 203-207
    8. Eric R. Switzer, Thomas M. Crawford, Christian L. Reichardt
      Pages 219-224
    9. Thomas J. Loredo
      Pages 225-236
  4. Data Mining and Astroinformatics

  5. Image and Time Series Analysis

    1. Front Matter
      Pages 327-327
    2. David Stenning, Vinay Kashyap, Thomas C. M. Lee, David A. van Dyk, C. Alex Young
      Pages 329-342
    3. Andrew Connolly, John Peterson, Garret Jernigan, D. Bard, the LSST Image Simulation Group
      Pages 347-359
    4. Erik Rosolowsky
      Pages 367-382
    5. Nicolle Clements, Sanat K. Sarkar, Wenge Guo
      Pages 383-396
    6. Debashis Mondal, Donald B. Percival
      Pages 403-418
  6. The Future of Astrostatistics

    1. Front Matter
      Pages 425-425
    2. Joseph M. Hilbe
      Pages 427-433
    3. Luke Tierney
      Pages 435-447
  7. Contributed Papers

    1. Front Matter
      Pages 467-467
    2. Paul D. Baines, Irina S. Udaltsova, Andreas Zezas, Vinay L. Kashyap
      Pages 469-472

About these proceedings


Now beginning its third decade, the Statistical Challenges in Modern Astronomy (SCMA) conferences are the premier forums where astronomers and statisticians discuss advanced methodological issues arising in astronomical research.  From cosmology to exoplanets, astronomers produce enormous datasets and encounter difficult modeling issues to arrive at astrophysical insights.  At the SCMA V conference held at Penn State University in June 2011, researchers from around the world presented the latest astrostatistical methods.  To promote cross-disciplinary perspectives, each lecture from an expert in one field is followed by a commentary from the other field.

A wide range of statistical developments are highlighted in the SCMA V conference.  Some focus on problems arising in precision cosmology involving characteristics of the cosmic microwave background, galaxy clustering and gravitational lensing.  Bayesian approaches are particularly important in this and other areas.  Knowledge discovery from megadatasets brings methods of data mining into use. Image analysis and time series analysis are areas where astronomers perennially wrestle with sophisticated modeling problems.  The proceedings ends with discussion of the future of astrostatistics. 

Eric D. Feigelson, Professor of Astronomy & Astrophysics, and G. Jogesh Babu, Professor of Statistics, have long collaborated in cross-disciplinary research and services.  Under the auspices of Penn State's Center for Astrostatistics, they run the SCMA conferences, offer summer schools in statistics for astronomers, produce texts and research articles promoting advances in statistical methodology in astronomy.  Feigelson also conducts research in X-ray astronomy and star formation, and Babu is a mathematical statistician with interest in bootstrap methods, nonparametrics and asymptotic theory.


Digitized sky surveys Poission processes Statistical astronomy Wave-let forms

Editors and affiliations

  • Eric D. Feigelson
    • 1
  • G. Jogesh Babu
    • 2
  1. 1., Dept. Astronomy & AstrophysicsPennsylvania State UniversityUniversity ParkUSA
  2. 2., Department of StatisticsPennsylvania State UniversityUniversity ParkUSA

Bibliographic information

  • DOI
  • Copyright Information Springer Science+Business Media New York 2012
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4614-3519-8
  • Online ISBN 978-1-4614-3520-4
  • Series Print ISSN 0930-0325
  • Buy this book on publisher's site