Modern Statistical Methods for Astronomy

Erscheinungsjahr 2017
ISBN: 978-0-521-76727-9
Verlag: Cambridge University Press

Buch, Englisch, 490 Seiten, Format (B × H): 208 mm x 260 mm, Gewicht: 1292 g

Modern astronomical research is beset with a vast range of statistical challenges, ranging from reducing data from megadatasets to characterizing an amazing variety of variable celestial objects or testing astrophysical theory. Linking astronomy to the world of modern statistics, this volume is a unique resource, introducing astronomers to advanced statistics through ready-to-use code in the public domain R statistical software environment. The book presents fundamental results of probability theory and statistical inference, before exploring several fields of applied statistics, such as data smoothing, regression, multivariate analysis and classification, treatment of nondetections, time series analysis, and spatial point processes. It applies the methods discussed to contemporary astronomical research datasets using the R statistical software, making it invaluable for graduate students and researchers facing complex data analysis tasks. A link to the author's website for this book can be found at www.cambridge.org/msma. Material available on their website includes datasets, R code and errata.

Autoren/Hrsg.

Feigelson, Eric D.

Babu, G. Jogesh

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Naturwissenschaften Physik Physik Allgemein Theoretische Physik, Mathematische Physik, Computerphysik
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
• Naturwissenschaften Astronomie Astronomie: Allgemeines
• Naturwissenschaften Astronomie Astrophysik
• Naturwissenschaften Physik Angewandte Physik Astrophysik

Inhaltsverzeichnis

1. Introduction; 2. Probability; 3. Statistical inference; 4. Probability distribution functions; 5. Nonparametric statistics; 6. Density estimation or data smoothing; 7. Regression; 8. Multivariate analysis; 9. Clustering, classification and data mining; 10. Nondetections: censored and truncated data; 11. Time series analysis; 12. Spatial point processes; Appendices; Index.

Über Autor(innen)

Babu, G. Jogesh
G. Jogesh Babu is Professor of Statistics and Director of the Center for Astrostatistics at Pennsylvania State University. He has made extensive contributions to probabilistic number theory, resampling methods, nonparametric methods, asymptotic theory and applications to biomedical research, genetics, astronomy and astrophysics.

Feigelson, Eric D.
Eric D. Feigelson is a Professor in the Department of Astronomy and Astrophysics at Pennsylvania State University. He is a leading observational astronomer and has worked with statisticians for twenty-five years to bring advanced methodology to problems in astronomical research.