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Author: Joseph M. Hilbe
Publisher: Cambridge University Press
Published: 2017-04-27
Total Pages: 429
ISBN-13: 1107133084
DOWNLOAD EBOOKA hands-on guide to Bayesian models with R, JAGS, Python, and Stan code, for a wide range of astronomical data types.
Author: Joseph M. Hilbe
Publisher: Cambridge University Press
Published: 2017-04-27
Total Pages: 429
ISBN-13: 1108210740
DOWNLOAD EBOOKThis comprehensive guide to Bayesian methods in astronomy enables hands-on work by supplying complete R, JAGS, Python, and Stan code, to use directly or to adapt. It begins by examining the normal model from both frequentist and Bayesian perspectives and then progresses to a full range of Bayesian generalized linear and mixed or hierarchical models, as well as additional types of models such as ABC and INLA. The book provides code that is largely unavailable elsewhere and includes details on interpreting and evaluating Bayesian models. Initial discussions offer models in synthetic form so that readers can easily adapt them to their own data; later the models are applied to real astronomical data. The consistent focus is on hands-on modeling, analysis of data, and interpretations that address scientific questions. A must-have for astronomers, its concrete approach will also be attractive to researchers in the sciences more generally.
Author: Michael P. Hobson
Publisher: Cambridge University Press
Published: 2010
Total Pages: 317
ISBN-13: 0521887941
DOWNLOAD EBOOKComprehensive introduction to Bayesian methods in cosmological studies, for graduate students and researchers in cosmology, astrophysics and applied statistics.
Author: Andrés Asensio Ramos
Publisher:
Published: 2018
Total Pages:
ISBN-13: 9781107499584
DOWNLOAD EBOOK"Bayesian methods are increasingly being employed in many different areas of physical sciences research. In astrophysics, models are used to make predictions to compare to observations that are incomplete and uncertain, so the comparison must be pursued by following a probabilistic approach. With contributions from leading experts, this volume covers the foundations of Bayesian inference, a description of the applicable computational methods, and recent results from their application to areas such as exoplanet detection and characterisation, image reconstruction, and cosmology. With content that appeals both to young researchers seeking to learn about Bayesian methods and to astronomers wishing to incorporate these approaches into their research, it provides the next generation of researchers with tools of modern data analysis that are becoming standard in astrophysical research"--
Author: Stefano Andreon
Publisher: Springer
Published: 2015-05-19
Total Pages: 245
ISBN-13: 3319152874
DOWNLOAD EBOOKStatistical literacy is critical for the modern researcher in Physics and Astronomy. This book empowers researchers in these disciplines by providing the tools they will need to analyze their own data. Chapters in this book provide a statistical base from which to approach new problems, including numerical advice and a profusion of examples. The examples are engaging analyses of real-world problems taken from modern astronomical research. The examples are intended to be starting points for readers as they learn to approach their own data and research questions. Acknowledging that scientific progress now hinges on the availability of data and the possibility to improve previous analyses, data and code are distributed throughout the book. The JAGS symbolic language used throughout the book makes it easy to perform Bayesian analysis and is particularly valuable as readers may use it in a myriad of scenarios through slight modifications. This book is comprehensive, well written, and will surely be regarded as a standard text in both astrostatistics and physical statistics. Joseph M. Hilbe, President, International Astrostatistics Association, Professor Emeritus, University of Hawaii, and Adjunct Professor of Statistics, Arizona State University
Author: Joseph M. Hilbe
Publisher: Cambridge University Press
Published: 2014-07-21
Total Pages: 301
ISBN-13: 1107028337
DOWNLOAD EBOOKThis book provides guidelines and fully worked examples of how to select, construct, interpret and evaluate the full range of count models.
Author: Eric D. Feigelson
Publisher: Cambridge University Press
Published: 2012-07-12
Total Pages: 495
ISBN-13: 052176727X
DOWNLOAD EBOOKModern Statistical Methods for Astronomy: With R Applications.
Author: Peter Congdon
Publisher: John Wiley & Sons
Published: 2005-12-13
Total Pages: 446
ISBN-13: 0470092386
DOWNLOAD EBOOKThe use of Bayesian methods for the analysis of data has grown substantially in areas as diverse as applied statistics, psychology, economics and medical science. Bayesian Methods for Categorical Data sets out to demystify modern Bayesian methods, making them accessible to students and researchers alike. Emphasizing the use of statistical computing and applied data analysis, this book provides a comprehensive introduction to Bayesian methods of categorical outcomes. * Reviews recent Bayesian methodology for categorical outcomes (binary, count and multinomial data). * Considers missing data models techniques and non-standard models (ZIP and negative binomial). * Evaluates time series and spatio-temporal models for discrete data. * Features discussion of univariate and multivariate techniques. * Provides a set of downloadable worked examples with documented WinBUGS code, available from an ftp site. The author's previous 2 bestselling titles provided a comprehensive introduction to the theory and application of Bayesian models. Bayesian Models for Categorical Data continues to build upon this foundation by developing their application to categorical, or discrete data - one of the most common types of data available. The author's clear and logical approach makes the book accessible to a wide range of students and practitioners, including those dealing with categorical data in medicine, sociology, psychology and epidemiology.
Author: Andrés Asensio Ramos
Publisher: Cambridge University Press
Published: 2018-04-26
Total Pages: 209
ISBN-13: 1107102138
DOWNLOAD EBOOKProvides an overview of the fundamentals of Bayesian inference and its applications within astrophysics, for graduate students and researchers.
Author: Eric D. Feigelson
Publisher: Springer Science & Business Media
Published: 2006-05-26
Total Pages: 512
ISBN-13: 0387215298
DOWNLOAD EBOOKDigital 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.
