附註:Includes bibliographical references and index.
1. Statistical Challenge in Medieval (and Later) Astronomy / Virginia Trimble -- 2. Power from Understanding the Shape of Measurement : Progress in Bayesian Inference for Astrophysics / Alanna Connors -- Commentary by Eric D. Kolaczyk -- 3. Hierarchical Models, Data Augmentation, and Markov Chain Monte Carlo / David A. van Dyk -- Commentary by Michael A. Strauss -- 4. Bayesian Adaptive Exploration / Thomas J. Loredo and David F. Chernoff -- Commentary by David A. van Dyk -- 5. Bayesian Model Selection and Analysis for Cepheid Star Oscillations / James O. Berger et al. -- Commentary by Thomas J. Loredo -- 6. Bayesian Multiscale Methods for Poisson Count Data / Eric D. Kolaczyk -- 7. NASA's Astrophysics Data Environment / Joseph H. Bredekamp and Daniel A. Golombek -- 8. Statistical and Astronomical Challenges in the Sloan Digital Sky Survey / Michael A. Strauss -- Commentary by David A. van Dyk -- 9. Challenges for Cluster Analysis in a Virtual Observatory / S.G. Djorgovski et al. -- Commentary by Dianne Cook -- 10. Statistics of Galaxy Clustering / Vicent J. Martinez and Enn Saar -- Commentary by Rien van de Weygaert -- 11. Analyzing Large Data Sets in Cosmology / Alexander S. Szalay and Takahiko Matsubara -- 12. The Cosmic Foam : Stochastic Geometry and Spatial Clustering across the Universe / Rien ven de Weygaert -- 13. Statistics and the Cosmic Microwave Background / Andrew H. Jaffe -- Commentary by PICA -- 14. Inference in Microwave Cosmology : A Frequentist Perspective / Chad M. Schafer and Philip B. Stark -- Commentary by Andrew H. Jaffe -- 15. Nonparametric Inference in Astrophysics / Pittsburgh Institute for Computational Astrostatistics (PICA) -- Commentary by Michael A. Strauss -- Commentary by Jeffrey D. Scargle -- Rejoinder by PICA -- 16. Random Forests : Finding Quasars / Leo Breiman et al. -- Commentary by Eric D. Feigelson -- 17. Interactive and Dynamic Graphics for Data Analysis : A Case Study On Quasar Data / Dianne Cook -- Commentary by Fionn D.
Contains papers from the third Statistical Challenges in Modern Astronomy (SCMA III) conference held at Penn State University, July 18-21 2001.
摘要: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.
