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Statistical Challenges in Astronomy

  • Conference proceedings
  • © 2003

Overview

Authors:
  1. Eric D. Feigelson

    1. Department of Astronomy and Astrophysics, Pennsylvania State University, University Park, USA

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  2. G. Jogesh Babu

    1. Department of Statistics, Pennsylvania State University, University Park, USA

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    You can also search for this author in PubMed   Google Scholar

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Table of contents (67 papers)

  1. Front Matter

    Pages i-xxii
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  2. Statistical Challenge in Medieval (and Later) Astronomy

    • Virginia Trimble
    Pages 1-18

  3. Power from Understanding the Shape of Measurement: Progress in Bayesian Inference for Astrophysics

    • A. Connors
    Pages 19-39

  4. Hierarchical Models, Data Augmentation, and Markov Chain Monte Carlo

    • David A. van Dyk
    Pages 41-55

  5. Bayesian Adaptive Exploration

    • Thomas J. Loredo, David F. Chernoff
    Pages 57-70

  6. Bayesian Model Selection and Analysis for Cepheid Star Oscillations

    • James O. Berger, William H. Jefferys, Peter Muller, Thomas G. Barnes
    Pages 71-88

  7. Bayesian Multiscale Methods for Poisson Count Data

    • Eric D. Kolaczyk
    Pages 89-102

  8. NASA’s Astrophysics Data Environment

    • Joseph H. Bredekamp, Daniel A. Golombek
    Pages 103-112

  9. Statistical and Astronomical Challenges in the Sloan Digital Sky Survey

    • Michael A. Strauss
    Pages 113-126

  10. Challenges for Cluster Analysis in a Virtual Observatory

    • S. G. Djorgovski, R. Brunner, A. Mahabal, R. Williams, R. Granat, P. Stolorz
    Pages 127-141

  11. Statistics of Galaxy Clustering

    • Vicent J. Martínez, Enn Saar
    Pages 143-160

  12. Analyzing Large Data Sets in Cosmology

    • Alexander S. Szalay, Takahiko Matsubara
    Pages 161-174

  13. The Cosmic Foam: Stochastic Geometry and Spatial Clustering across the Universe

    • Rien van de Weygaert
    Pages 175-196

  14. Statistics and the Cosmic Microwave Background

    • Andrew H. Jaffe
    Pages 197-214

  15. Inference in Microwave Cosmology: A Frequentist Perspective

    • Chad M. Schafer, Philip B. Stark
    Pages 215-219

  16. Nonparametric Inference in Astrophysics

    • The Pittsburgh Institute for Computational Astrostatistics (PICA)
    Pages 221-241

  17. Random Forests: Finding Quasars

    • Leo Breiman, Michael Last, John Rice
    Pages 243-254

  18. Interactive and Dynamic Graphics for Data Analysis: A Case Study On Quasar Data

    • Dianne Cook
    Pages 255-264

  19. Computational AstroStatistics: Fast and Efficient Tools for Analysing Huge Astronomical Data Sources

    • Robert C. Nichol, S. Chong, A. J. Connolly, S. Davies, C. Genovese, A. M. Hopkins et al.
    Pages 265-278

  20. Clustering in High-Dimensional Data Spaces

    • Fionn D. Murtagh
    Pages 279-292
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Keywords

About this book

Digital sky surveys, high-precision astrometry from satellite data, deep-space data from orbiting telescopes, and the like have all increased the quantity and quality of astronomical data by orders of magnitude per year for several years. Making sense of this wealth of data requires sophisticated statistical techniques. Fortunately, statistical methodologies have similarly made great strides in recent years. Powerful synergies thus emerge when astronomers and statisticians join in examining astrostatistical problems and approaches.

The book begins with an historical overview and tutorial articles on basic cosmology for statisticians and the principles of Bayesian analysis for astronomers. As in earlier volumes in this series, research contributions discussing topics in one field are joined with commentary from scholars in the other. Thus, for example, an overview of Bayesian methods for Poissonian data is joined by discussions of planning astronomical observations with optimal efficiency and nested models to deal with instrumental effects.

The principal theme for the volume is the statistical methods needed to model fundamental characteristics of the early universe on its largest scales.

Authors and Affiliations

  • Department of Astronomy and Astrophysics, Pennsylvania State University, University Park, USA

    Eric D. Feigelson

  • Department of Statistics, Pennsylvania State University, University Park, USA

    G. Jogesh Babu

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