Astrostatistical Challenges for the New Astronomy

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Hilbe, Joseph M. (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: New York, NY : Springer New York : Imprint: Springer, 2013.
• Σειρά: Springer Series in Astrostatistics ; 1
• Θέματα: Statistics.; Astronomy.; Astrophysics.; Cosmology.; Statistical Theory and Methods.; Statistics and Computing/Statistics Programs.; Astronomy, Astrophysics and Cosmology.

 Astrostatistical Challenges for the New Astronomy presents a collection of monographs authored by several of the disciplines leading astrostatisticians, i.e. by researchers from the fields of statistics and astronomy-astrophysics having in interest in the statistical analysis of astronomical and cosmological data.  Eight of the ten monographs are enhancements of presentations given by the authors as invited or special topics in astrostatistics papers at the ISI World Statistics Congress (2011, Dublin, Ireland). The opening chapter, by the editor, was adapted from an invited seminar given at Los Alamos National Laboratory (2011) on the history and current state of the discipline; the second chapter by Thomas Loredo was adapted from his invited presentation at the Statistical Challenges in Modern Astronomy V conference (2011, Pennsylvania State University), presenting insights regarding frequentist and Bayesian methods of estimation in astrostatistical analysis. The remaining monographs are research papers discussing various topics in astrostatistics. The monographs provide the reader with an excellent overview of the current state astrostatistical research, and offer guidelines as to subjects of future research. 

 Joseph Hilbe, Jet Propulsion Laboratory and Arizona State University, Astrostatistics: A brief history and view to the future -- Thomas Loredo, Cornell Univ, Bayesian astrostatistics: A backward look to the future -- Stefano Andreon, INAF-Osservatorio Astronomico di Brera, Italy, Understanding better (some) astronomical data using Bayesian methods -- Martin Kunz, Institute for Theoretical Physics, Univ of Geneva, BEAMS: separating the wheat from the chaff in supernova analysis -- Benjamin Wandelt, Institut d'Astrophysique de Paris, Université Pierre et Marie Curie, France, Cosmostatistics -- Roberto Trotta, Astrophysics Group, Dept of Physics, Imperial College London  (with Farhan Feroz (Cambridge), Mike Hobson (Cambridge), and Roberto Ruiz de Austri (Univ of Valencia, Spain), Recent advances in Bayesian inference in cosmology and astroparticle physics thanks to the Multinest Algorithm -- Phillip Gregory, Department of Astronomy, Univ of British Columbia, Canada, Extrasolar planets via Bayesian model fitting -- Marc Henrion, Dept of Mathematics, Imperial College, London, UK (with Daniel Mortlock (Imperial), Axel Gandy (Imperial), and David J. Hand (Imperial)), Subspace methods for anomaly detection in high dimensional astronomical databases -- Asis Kumar Chattopadhyay, Dept of Statistics, Univ of Calcutta, India (with Tanuka Chattyopadhyay, Tuli De, and Saptarshi Mondal), Independent Component Analysis for dimension reduction classification: Hough transform and CASH Algorithm -- Marisa March, Astrophysics Group, Dept of Physics, Imperial College London (with Roberto Trotta), Improved cosmological constraints from a Bayesian hierarchical model of supernova type Ia data                                                                                                                                                                                                                                                          .