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Statistical Challenges in Astronomy

  • Eric D. Feigelson
  • G. Jogesh Babu

Table of contents

  1. Front Matter
    Pages i-xxii
  2. Thomas J. Loredo, David F. Chernoff
    Pages 57-70
  3. James O. Berger, William H. Jefferys, Peter Muller, Thomas G. Barnes
    Pages 71-88
  4. Joseph H. Bredekamp, Daniel A. Golombek
    Pages 103-112
  5. S. G. Djorgovski, R. Brunner, A. Mahabal, R. Williams, R. Granat, P. Stolorz
    Pages 127-141
  6. Vicent J. Martínez, Enn Saar
    Pages 143-160
  7. Alexander S. Szalay, Takahiko Matsubara
    Pages 161-174
  8. Andrew H. Jaffe
    Pages 197-214
  9. Chad M. Schafer, Philip B. Stark
    Pages 215-219
  10. The Pittsburgh Institute for Computational Astrostatistics (PICA)
    Pages 221-241
  11. Leo Breiman, Michael Last, John Rice
    Pages 243-254
  12. Robert C. Nichol, S. Chong, A. J. Connolly, S. Davies, C. Genovese, A. M. Hopkins et al.
    Pages 265-278
  13. Fionn D. Murtagh
    Pages 279-292
  14. Jean-Luc Starck
    Pages 331-342
  15. Iain Johnstone
    Pages 343-364
  16. Peter E. Freeman, V. Kashyap, R. Rosner, D. Q. Lamb
    Pages 365-376
  17. John Rice
    Pages 377-386
  18. Joseph Silk
    Pages 387-394
  19. D. Bazell
    Pages 395-396
  20. S. P. Bhavsar, J. P. Bernstein
    Pages 397-398
  21. Yaoquan Chu, XiaoHu Yang, Long-Long Feng, Li-Zhi Fang
    Pages 401-402
  22. A. Connors, A. Carramiñana
    Pages 403-408
  23. A. Del Popolo
    Pages 412-414
  24. S. Derriere, F. Ochsenbein, D. Egret
    Pages 415-416
  25. A. Doroshkevich
    Pages 417-418
  26. J. Gallegos, E. Martínez-González, F. Argüeso, L. Cayón, J.L. Sanz
    Pages 421-422
  27. J. Greenhough, S. C. Chapman, S. Chaty, R. O. Dendy, G. Rowlands
    Pages 423-424
  28. Christopher Hans, David A. van Dyk
    Pages 429-430
  29. Evanthia Hatziminaoglou, EIS team
    Pages 431-432
  30. G. Hawkins, J. A. Mattei, G. Foster
    Pages 433-434
  31. William H. Jefferys
    Pages 447-448
  32. Hosung Kang, David A. van Dyk, Yaming Yu, Aneta Siemiginowska, Alanna Connors, Vinay L. Kashyap
    Pages 449-450
  33. Vinay Kashyap, Jeremy J. Drake, Manuel Güdel, Marc Audard
    Pages 451-452
  34. V. G. Laidler, R. L. White
    Pages 453-455

About these proceedings

Introduction

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.

Keywords

Astrometry Astronomical Observation Cluster analysis Cosmology Galaxy Star Time series Universe astronomy clustering data analysis quasar

Authors and affiliations

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

Bibliographic information