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Statistical Challenges in Modern Astronomy V

  • Conference proceedings
  • © 2012

Overview

Editors:
  1. Eric D. Feigelson

    1. , Dept. Astronomy & 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 editor in PubMed   Google Scholar

  • Covers wide range of advances in statistical astronomy
  • Many new techniques in the areas of large data set star and planet mapping will be discussed, including time series and applications in SAS and R
  • Documents a successful symposium on statistical astronomy
  • Includes supplementary material: sn.pub/extras

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

Part of the book sub series: Lecture Notes in Statistics - Proceedings (LNSP)

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About this book

This volume contains a selection of chapters based on papers to be presented at the Fifth Statistical Challenges in Modern Astronomy Symposium. The symposium will be held June 13-15th at Penn State University. Modern astronomical research faces a vast range of statistical issues which have spawned a revival in methodological activity among astronomers. The Statistical Challenges in Modern Astronomy V conference will bring astronomers and statisticians together to discuss methodological issues of common interest. Time series analysis, image analysis, Bayesian methods, Poisson processes, nonlinear regression, maximum likelihood, multivariate classification, and wavelet and multiscale analyses are all important themes to be covered in detail. Many problems will be introduced at the conference in the context of large-scale astronomical projects including LIGO, AXAF, XTE, Hipparcos, and digitized sky surveys.

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Keywords

Table of contents (67 papers)

  1. Front Matter

    Pages i-xxiii
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  2. Statistics in Cosmology

    1. Front Matter

      Pages 1-1
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    2. Likelihood-Free Inference in Cosmology: Potential for the Estimation of Luminosity Functions

      • Chad M. Schafer, Peter E. Freeman
      Pages 3-19

    3. Commentary: Likelihood-Free Inference in Cosmology: Potential for the Estimation of Luminosity Functions

      • Martin A. Hendry
      Pages 21-25

    4. Robust, Data-Driven Inference in Non-linear Cosmostatistics

      • Benjamin D. Wandelt, Jens Jasche, Guilhem Lavaux
      Pages 27-40

    5. Simulation-Aided Inference in Cosmology

      • David Higdon, Earl Lawrence, Katrin Heitmann, Salman Habib
      Pages 41-57

    6. Commentary: Simulation-Aided Inference in Cosmology

      • Carlo Graziani
      Pages 59-64

    7. The Matter Spectral Density from Lensed Cosmic Microwave Background Observations

      • Ethan Anderes, Alexander van Engelen
      Pages 65-77

    8. Commentary: ‘The Matter Spectral Density from Lensed Cosmic Microwave Background Observations’

      • Alan Heavens
      Pages 79-82

    9. Needlets Estimation in Cosmology and Astrophysics

      • Domenico Marinucci
      Pages 83-97

  3. Bayesian Analysis Across Astronomy

    1. Front Matter

      Pages 99-99
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  4. Bayesian Analysis Across Astronomy

    1. Parameter Estimation and Model Selection in Extragalactic Astronomy

      • Martin D. Weinberg
      Pages 101-116

    2. Commentary: Bayesian Model Selection and Parameter Estimation

      • Philip C. Gregory
      Pages 117-125

    3. Cosmological Bayesian Model Selection: Recent Advances and Open Challenges

      • Roberto Trotta
      Pages 127-140

    4. Commentary: Cosmological Bayesian Model Selection

      • David A. van Dyk
      Pages 141-146

    5. Measurement Error Models in Astronomy

      • Brandon C. Kelly
      Pages 147-162

    6. Commentary: “Measurement Error Models in Astronomy” by Brandon C. Kelly

      • David Ruppert
      Pages 163-169

    7. Asteroseismology: Bayesian Analysis of Solar-Like Oscillators

      • Othman Benomar
      Pages 171-176

    8. Semi-parametric Robust Event Detection for Massive Time-Domain Databases

      • Alexander W. Blocker, Pavlos Protopapas
      Pages 177-187

    9. Bayesian Analysis of Reverberation Mapping Data

      • Brendon J. Brewer
      Pages 189-195
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Editors and Affiliations

  • , Dept. Astronomy & Astrophysics, Pennsylvania State University, University Park, USA

    Eric D. Feigelson

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

    G. Jogesh Babu

About the editors

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.  

 

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