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ISBN: | 7229286818 |

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- Statistical Challenges in Modern Astronomy IV — Astrostatistics and Astroinformatics Portal
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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. To promote cross-disciplinary perspectives, each lecture from an expert in one field is followed by a commentary from the other field.

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. Jogesh Babu, Professor of Statistics, have long collaborated in cross-disciplinary research and services.

Modern astronomical research faces a vast range of statistical issues which have spawned a revival in methodological Part IV Image and Time Series Analysis.

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. Skip to main content Skip to table of contents. Advertisement Hide. Statistical Challenges in Modern Astronomy V.

Editors view affiliations Eric D. Feigelson G. Conference proceedings. Front Matter Pages i-xxiii. Front Matter Pages Pages Benjamin D. Wandelt, Jens Jasche, Guilhem Lavaux. Simulation-Aided Inference in Cosmology. Commentary: Simulation-Aided Inference in Cosmology. Needlets Estimation in Cosmology and Astrophysics. Commentary: Cosmological Bayesian Model Selection. Measurement Error Models in Astronomy.

Alexander W. Blocker, Pavlos Protopapas. Bayesian Analysis of Reverberation Mapping Data. Systematic Errors in High-Energy Astrophysics.

Time series analysis is discussed in a variety of contexts: sparse Poisson data, multiply-periodic systems, gravitational wave detection, and most dramatically in the search for extrasolar planets. The methodological challenges of inferring cosmological insights from the cosmic microwave background fluctuations, the distribution of galaxies in space, gravitational lensing, and galaxy structure wre describe in detail. The volume ends with cross-disciplinary overviews and software tutorials. Both astronomical and statistical communities now recognize the wide array of fascinating methodological issues faced by the modern astronomer. Ranging from terabyte wide-field surveys to small-N samples, from cosmology to the search for Earth-like planets, astronomical research can no longer be pursued with a small toolbox of familiar statistical methods. Other topics covered include image processing, analysis of mega-datasets from large surveys, and small-N problems in both astronomy and particle physics. Over thirty distinguished scholars from both fields presented invited talks and commentaries on leading problems in astrostatistics. Gutti Jogesh Babu , Eric D.

Eric R. Switzer, Thomas M. Crawford, Christian L. Commentary: Bayesian Analysis Across Astronomy. Sparse Astronomical Data Analysis. Surprise Detection in Multivariate Astronomical Data. On Statistical Cross-Identification in Astronomy. Data Compression Methods in Astrophysics.

Commentary: Data Compression Methods in Astrophysics. Morphological Image Analysis and Sunspot Classification. Lee, David A. Alex Young. Learning About the Sky Through Simulations. Statistical Analyses of Data Cubes. Nicolle Clements, Sanat K. Sarkar, Wenge Guo. Astrostatistics in the International Arena. The R Statistical Computing Environment. Panel Discussion: The Future of Astrostatistics. Bayesian Estimation of log N — log S.

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- Statistical challenges in modern astronomy iv.
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Baines, Irina S. Udaltsova, Andreas Zezas, Vinay L. About these proceedings Introduction 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.

Digitized sky surveys Poission processes Statistical astronomy Wave-let forms. Editors and affiliations. Feigelson 1 G. Buy options.

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