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Statistical Challenges in Astronomy
 
 
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Statistical Challenges in Astronomy [Hardcover]

Eric D. Feigelson (Editor), G Jogesh Babu (Editor)

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Book Description

0387955461 978-0387955469 January 14, 2003 1
Digital sky surveys, high-precision astrometry from satellite data, deep-space data from orbiting telescopes, and the like have all increased the quantity and quality of astronomical data by orders of magnitude per year for several years. Making sense of this wealth of data requires sophisticated statistical techniques. Fortunately, statistical methodologies have similarly made great strides in recent years. Powerful synergies thus emerge when astronomers and statisticians join in examining astrostatistical problems and approaches. The book begins with an historical overview and tutorial articles on basic cosmology for statisticians and the principles of Bayesian analysis for astronomers. As in earlier volumes in this series, research contributions discussing topics in one field are joined with commentary from scholars in the other. Thus, for example, an overview of Bayesian methods for Poissonian data is joined by discussions of planning astronomical observations with optimal efficiency and nested models to deal with instrumental effects. The principal theme for the volume is the statistical methods needed to model fundamental characteristics of the early universe on its largest scales.

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Inside This Book (learn more)
First Sentence:
ABSTRACT Portions of the history of the interaction between astronomy and statistics are told in the form of short case studies of a number of people who appear (or should appear) in books about both. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
radio peak flux, massive vertices, weighted power spectrum, cosmic matter distribution, lefthand frame, uniformly sampled data, cosmic foam, ridgelet transform, effective dwell time, frequentist calculations, righthand frame, red magnitude, trous algorithm, bayesian experimental design, adaptive exploration, redshift space distortions, large redshift surveys, galaxy distribution, surrogate data sets, timing residuals, true power spectrum, clustering length, quadrature data, frequentist analyses, clustering strength
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Sloan Digital Sky Survey, Bayesian Blocks, Dianne Cook, Mexican Hat, Milky Way, The Astrophysical Journal, John Wiley, Enn Saar, Bayes Network, Del Popolo, Jean-Luc Starck, Phys Rev, The Annals of Statistics, Astronomical Time Series Analysis, Bell Labs, Big Bang, Bob Nichol, Harvard University, San Francisco, Cambridge University Press, Journal of the American Statistical Association, Journal of the Royal Statistical Society, Larry Bretthorst, Office of Space Science
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