Modern statistical methods for astronomy : with R applications /

"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. Yet most astronomers still use a narrow suite of traditional stati...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Feigelson, Eric D.
Otros Autores: Babu, Gutti Jogesh, 1949-
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cambridge : Cambridge University Press, 2012.
Temas:
Statistical astronomy.
Statistique stellaire.
SCIENCE > Astronomy.
Acceso en línea:Texto completo

MARC

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100 1 |a Feigelson, Eric D. 
245 1 0 |a Modern statistical methods for astronomy :  |b with R applications /  |c Eric D. Feigelson, G. Jogesh Babu. 
264 1 |a Cambridge :  |b Cambridge University Press,  |c 2012. 
264 4 |c Ã2012 
300 |a 1 online resource (xviii, 476 pages) :  |b illustrations (some color) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
504 |a Includes bibliographical references (pages 434-461) and index. 
520 |a "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. Yet most astronomers still use a narrow suite of traditional statistical methods. 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."--  |c Provided by publisher. 
586 |a Association of American Publishers PROSE Award, 2012. 
588 0 |a Print version record. 
505 0 |a Cover; Modern Statistical Methods for Astronomy; Title; Copyright; Dedication; Contents; Preface; Motivation and goals; Audience; Outline and classroom use; Astronomical datasets and R scripts; Acknowledgements; 1: Introduction; 1.1 The role of statistics in astronomy; 1.1.1 Astronomy and astrophysics; 1.1.2 Probability and statistics; 1.1.3 Statistics and science; 1.2 History of statistics in astronomy; 1.2.1 Antiquity through the Renaissance; 1.2.2 Foundations of statistics in celestial mechanics; 1.2.3 Statistics in twentieth-century astronomy; 1.3 Recommended reading; 2: Probability. 
505 8 |a 2.1 Uncertainty in observational science2.2 Outcome spaces and events; 2.3 Axioms of probability; 2.4 Conditional probabilities; 2.4.1 Bayes' theorem; 2.4.2 Independent events; 2.5 Random variables; 2.5.1 Density and distribution functions; 2.5.2 Independent and identically distributed random variables; 2.6 Quantile function; 2.7 Discrete distributions; 2.8 Continuous distributions; 2.9 Distributions that are neither discrete nor continuous; 2.10 Limit theorems; 2.11 Recommended reading; 2.12 R applications; 3: Statistical inference; 3.1 The astronomical context. 
505 8 |a 3.2 Concepts of statistical inference3.3 Principles of point estimation; 3.4 Techniques of point estimation; 3.4.1 Method of moments; 3.4.2 Method of least squares; 3.4.3 Maximum likelihood method; 3.4.4 Confidence intervals; 3.4.5 Calculating MLEs with the EM algorithm; 3.5 Hypothesis testing techniques; 3.6 Resampling methods; 3.6.1 Jackknife; 3.6.2 Bootstrap; 3.7 Model selection and goodness-of-fit; 3.7.1 Nonparametric methods for goodness-of-fit; 3.7.2 Likelihood-based methods for model selection; 3.7.3 Information criteria for model selection; 3.7.4 Comparing different model families. 
505 8 |a 3.8 Bayesian statistical inference3.8.1 Inference for the binomial proportion; 3.8.2 Prior distributions; 3.8.3 Inference for Gaussian distributions; 3.8.4 Hypotheses testing and the Bayes factor; 3.8.5 Model selection and averaging; 3.8.6 Bayesian computation; 3.9 Remarks; 3.10 Recommended reading; 3.11 R applications; 4: Probability distribution functions; 4.1 Binomial and multinomial; 4.1.1 Ratio of binomial random variables; 4.2 Poisson; 4.2.1 Astronomical context; 4.2.2 Mathematical properties; 4.2.3 Poisson processes; 4.3 Normal and lognormal; 4.4 Pareto (power-law). 
505 8 |a 4.4.1 Least-squares estimation4.4.2 Maximum likelihood estimation; 4.4.3 Extensions of the power-law; 4.4.4 Multivariate Pareto; 4.4.5 Origins of power-laws; 4.5 Gamma; 4.6 Recommended reading; 4.7 R applications; 4.7.1 Comparing Pareto distribution estimators; 4.7.2 Fitting distributions to data; 4.7.3 Scope of distributions in R and CRAN; 5: Nonparametric statistics; 5.1 The astronomical context; 5.2 Concepts of nonparametric inference; 5.3 Univariate problems; 5.3.1 Kolmogorov-Smirnov and other e.d.f. tests; 5.3.2 Robust statistics of location; 5.3.3 Robust statistics of spread. 
546 |a English. 
590 |a eBooks on EBSCOhost  |b EBSCO eBook Subscription Academic Collection - Worldwide 
650 0 |a Statistical astronomy. 
650 6 |a Statistique stellaire. 
650 7 |a SCIENCE  |x Astronomy.  |2 bisacsh 
650 7 |a Statistical astronomy.  |2 fast  |0 (OCoLC)fst01132055 
700 1 |a Babu, Gutti Jogesh,  |d 1949- 
776 0 8 |i Print version:  |a Feigelson, Eric D.  |t Modern statistical methods for astronomy.  |d New York : Cambridge University Press, 2012  |z 9780521767279  |w (DLC) 2012009113  |w (OCoLC)784123773 
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