Modern Statistical Methods for Astronomy by Eric D. Feigelson
With R Applications

No critic rating

Waiting for minimum critic reviews

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. Visit the author's homepage at http://astrostatistics.psu.edu for more materials.
 

About Eric D. Feigelson

See more books from this Author
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.
 
Published July 12, 2012 by Cambridge University Press. 490 pages
Genres: Education & Reference, Science & Math. Non-fiction

Rate this book!

Add Review
×