Modern Statistical Methods for Astronomy: With R Applications

Eric D. Feigelson

ISBN 10: 052176727X / ISBN 13: 9780521767279

Published by Cambridge University Press, 2012

About this Item

This item is printed on demand. New copy - Usually dispatched within 5-9 working days 1270.

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Bibliographic Details

• Title: Modern Statistical Methods for Astronomy: With R Applications
• Publisher: Cambridge University Press
• Publication Date: 2012
• Language: English
• ISBN 10: 052176727X
• ISBN 13: 9780521767279
• Binding: Hardback
• Condition: New
• Weight: 1270 grams

About this title

Synopsis

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.

About the Authors

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.

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.