Statistical Challenges in Modern Astronomy V [electronic resource] /
Feigelson, Eric D.editor.
Babu, Jogesh.editor.
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.
Description based upon print version of record.
Includes bibliographical references and index.
Statistics in Cosmology -- Bayesian Analysis Across Astronomy -- Data Mining and Astroinformatics -- Image and Time Series Analysis -- The Future of Astrostatistics -- Contributed Papers.
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.
Statistics .
Statistics, general.
Statistics for Life Sciences, Medicine, Health Sciences.