Bayesian Astrophysics

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Bayesian Models for Astrophysical Data

Author : Joseph M. Hilbe
Publisher : Cambridge University Press
ISBN 13 : 1108210740
Total Pages : 429 pages
Book Rating : 4.1/5 (82 download)

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Book Synopsis Bayesian Models for Astrophysical Data by : Joseph M. Hilbe

Download or read book Bayesian Models for Astrophysical Data written by Joseph M. Hilbe and published by Cambridge University Press. This book was released on 2017-04-27 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 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.

Bayesian Astrophysics

Author : Andrés Asensio Ramos
Publisher : Cambridge University Press
ISBN 13 : 1108619835
Total Pages : 210 pages
Book Rating : 4.1/5 (86 download)

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Book Synopsis Bayesian Astrophysics by : Andrés Asensio Ramos

Download or read book Bayesian Astrophysics written by Andrés Asensio Ramos and published by Cambridge University Press. This book was released on 2018-04-26 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian methods are being increasingly employed in many different areas of research in the physical sciences. In astrophysics, models are used to make predictions to be compared to observations. These observations offer information that is incomplete and uncertain, so the comparison has to be pursued by following a probabilistic approach. With contributions from leading experts, this volume covers the foundations of Bayesian inference, a description of computational methods, and recent results from their application to areas such as exoplanet detection and characterisation, image reconstruction, and cosmology. It appeals to both young researchers seeking to learn about Bayesian methods as well as to astronomers wishing to incorporate these approaches in their research areas. It provides the next generation of researchers with the tools of modern data analysis that are already becoming standard in current astrophysical research.

Bayesian Methods in Cosmology

Author : Michael P. Hobson
Publisher : Cambridge University Press
ISBN 13 : 0521887941
Total Pages : 317 pages
Book Rating : 4.5/5 (218 download)

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Book Synopsis Bayesian Methods in Cosmology by : Michael P. Hobson

Download or read book Bayesian Methods in Cosmology written by Michael P. Hobson and published by Cambridge University Press. This book was released on 2010 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive introduction to Bayesian methods in cosmological studies, for graduate students and researchers in cosmology, astrophysics and applied statistics.

Bayesian Models for Astrophysical Data

Author : Joseph M. Hilbe
Publisher : Cambridge University Press
ISBN 13 : 1107133084
Total Pages : 429 pages
Book Rating : 4.1/5 (71 download)

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Book Synopsis Bayesian Models for Astrophysical Data by : Joseph M. Hilbe

Bayesian Methods for the Physical Sciences

Author : Stefano Andreon
Publisher : Springer
ISBN 13 : 3319152874
Total Pages : 245 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Bayesian Methods for the Physical Sciences by : Stefano Andreon

Download or read book Bayesian Methods for the Physical Sciences written by Stefano Andreon and published by Springer. This book was released on 2015-05-19 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical 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

Statistics for Astrophysics

Author : Jean-Baptiste Marquette
Publisher : EDP Sciences
ISBN 13 : 2759822753
Total Pages : 140 pages
Book Rating : 4.7/5 (598 download)

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Book Synopsis Statistics for Astrophysics by : Jean-Baptiste Marquette

Download or read book Statistics for Astrophysics written by Jean-Baptiste Marquette and published by EDP Sciences. This book was released on 2019-09-19 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the lectures given during the third session of the School of Statistics for Astrophysics that took place at Autrans, near Grenoble, in France, in October 2017. The subject is Bayesian Methodology. The interest of this statistical approach in astrophysics probably comes from its necessity and its success in determining the cosmological parameters from observations, especially from the cosmic background luctuations. The cosmological community has thus been very active in this field for many years. But the Bayesian methodology, complementary to the more classical frequentist one, has many applications in physics in general due to its ability to incorporate a priori knowledge into inference, such as uncertainty brought by the observational processes. The Bayesian approach becomes more and more widespread in the astrophysical literature. This book contains statistics courses on basic to advanced methods with practical exercises using the R environment, by leading experts in their field. This covers the foundations of Bayesian inference, Markov chain Monte Carlo technique, model building, Approximate Bayesian Computation (ABC) and Bayesian nonparametric inference and clustering.

Statistics for Astrophysics

Author : Didier Fraix‐burnet
Publisher : EDP Sciences
ISBN 13 : 9782759822744
Total Pages : 140 pages
Book Rating : 4.8/5 (227 download)

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Book Synopsis Statistics for Astrophysics by : Didier Fraix‐burnet

Download or read book Statistics for Astrophysics written by Didier Fraix‐burnet and published by EDP Sciences. This book was released on 2018-01-10 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the lectures given during the third session of the School of Statistics for Astrophysics that took place at Autrans, near Grenoble, in France, in October 2017. The subject is Bayesian Methodology. The interest of this statistical approach in astrophysics probably comes from its necessity and its success in determining the cosmological parameters from observations, especially from the cosmic background fluctuations. The cosmological community has thus been very active in this field for many years. But the Bayesian methodology, complementary to the more classical frequentist one, has many applications in physics in general due to its ability to incorporate a priori knowledge into inference, such as uncertainty brought by the observational processes. The Bayesian approach becomes more and more widespread in the astrophysical literature. This book contains statistics courses on basic to advanced methods with practical exercises using the R environment, by leading experts in their field. This covers the foundations of Bayesian inference, Markov chain Monte Carlo technique, model building, Approximate Bayesian Computation (ABC) and Bayesian nonparametric inference and clustering.

Statistical Challenges in Modern Astronomy V

Author : Eric D. Feigelson
Publisher : Springer Science & Business Media
ISBN 13 : 146143520X
Total Pages : 544 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Statistical Challenges in Modern Astronomy V by : Eric D. Feigelson

Download or read book Statistical Challenges in Modern Astronomy V written by Eric D. Feigelson and published by Springer Science & Business Media. This book was released on 2012-08-15 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains a selection of chapters based on papers to be presented at the Fifth Statistical Challenges in Modern Astronomy Symposium. The symposium will be held June 13-15th at Penn State University. Modern astronomical research faces a vast range of statistical issues which have spawned a revival in methodological activity among astronomers. The Statistical Challenges in Modern Astronomy V conference will bring astronomers and statisticians together to discuss methodological issues of common interest. Time series analysis, image analysis, Bayesian methods, Poisson processes, nonlinear regression, maximum likelihood, multivariate classification, and wavelet and multiscale analyses are all important themes to be covered in detail. Many problems will be introduced at the conference in the context of large-scale astronomical projects including LIGO, AXAF, XTE, Hipparcos, and digitized sky surveys.

Statistical Challenges in Astronomy

Author : Eric D. Feigelson
Publisher : Springer Science & Business Media
ISBN 13 : 0387215298
Total Pages : 512 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Statistical Challenges in Astronomy by : Eric D. Feigelson

Download or read book Statistical Challenges in Astronomy written by Eric D. Feigelson and published by Springer Science & Business Media. This book was released on 2006-05-26 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Statistics for Astrophysics

Author : Didier Fraix-Burnet
Publisher :
ISBN 13 : 9782759817290
Total Pages : 226 pages
Book Rating : 4.8/5 (172 download)

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Book Synopsis Statistics for Astrophysics by : Didier Fraix-Burnet

Download or read book Statistics for Astrophysics written by Didier Fraix-Burnet and published by . This book was released on 2015 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Bayesian Probability Theory

Author : Wolfgang von der Linden
Publisher : Cambridge University Press
ISBN 13 : 1139952463
Total Pages : 653 pages
Book Rating : 4.1/5 (399 download)

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Book Synopsis Bayesian Probability Theory by : Wolfgang von der Linden

Download or read book Bayesian Probability Theory written by Wolfgang von der Linden and published by Cambridge University Press. This book was released on 2014-06-12 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the basics to the forefront of modern research, this book presents all aspects of probability theory, statistics and data analysis from a Bayesian perspective for physicists and engineers. The book presents the roots, applications and numerical implementation of probability theory, and covers advanced topics such as maximum entropy distributions, stochastic processes, parameter estimation, model selection, hypothesis testing and experimental design. In addition, it explores state-of-the art numerical techniques required to solve demanding real-world problems. The book is ideal for students and researchers in physical sciences and engineering.

Astrostatistical Challenges for the New Astronomy

Author : Joseph M. Hilbe
Publisher : Springer Science & Business Media
ISBN 13 : 1461435080
Total Pages : 247 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Astrostatistical Challenges for the New Astronomy by : Joseph M. Hilbe

Download or read book Astrostatistical Challenges for the New Astronomy written by Joseph M. Hilbe and published by Springer Science & Business Media. This book was released on 2012-11-07 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Astrostatistical Challenges for the New Astronomy presents a collection of monographs authored by several of the disciplines leading astrostatisticians, i.e. by researchers from the fields of statistics and astronomy-astrophysics, who work in the statistical analysis of astronomical and cosmological data. Eight of the ten monographs are enhancements of presentations given by the authors as invited or special topics in astrostatistics papers at the ISI World Statistics Congress (2011, Dublin, Ireland). The opening chapter, by the editor, was adapted from an invited seminar given at Los Alamos National Laboratory (2011) on the history and current state of the discipline; the second chapter by Thomas Loredo was adapted from his invited presentation at the Statistical Challenges in Modern Astronomy V conference (2011, Pennsylvania State University), presenting insights regarding frequentist and Bayesian methods of estimation in astrostatistical analysis. The remaining monographs are research papers discussing various topics in astrostatistics. The monographs provide the reader with an excellent overview of the current state astrostatistical research, and offer guidelines as to subjects of future research. Lead authors for each chapter respectively include Joseph M. Hilbe (Jet Propulsion Laboratory and Arizona State Univ); Thomas J. Loredo (Dept of Astronomy, Cornell Univ); Stefano Andreon (INAF-Osservatorio Astronomico di Brera, Italy); Martin Kunz ( Institute for Theoretical Physics, Univ of Geneva, Switz); Benjamin Wandel ( Institut d'Astrophysique de Paris, Univ Pierre et Marie Curie, France); Roberto Trotta (Astrophysics Group, Dept of Physics, Imperial College London, UK); Phillip Gregory (Dept of Astronomy, Univ of British Columbia, Canada); Marc Henrion (Dept of Mathematics, Imperial College, London, UK); Asis Kumar Chattopadhyay (Dept of Statistics, Univ of Calcutta, India); Marisa March (Astrophysics Group, Dept of Physics, Imperial College, London, UK)./body

Bayesian Logical Data Analysis for the Physical Sciences

Author : Phil Gregory
Publisher : Cambridge University Press
ISBN 13 : 113944428X
Total Pages : 498 pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Bayesian Logical Data Analysis for the Physical Sciences by : Phil Gregory

Download or read book Bayesian Logical Data Analysis for the Physical Sciences written by Phil Gregory and published by Cambridge University Press. This book was released on 2005-04-14 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book provides a clear exposition of the underlying concepts with many worked examples and problem sets. It also discusses implementation, including an introduction to Markov chain Monte-Carlo integration and linear and nonlinear model fitting. Particularly extensive coverage of spectral analysis (detecting and measuring periodic signals) includes a self-contained introduction to Fourier and discrete Fourier methods. There is a chapter devoted to Bayesian inference with Poisson sampling, and three chapters on frequentist methods help to bridge the gap between the frequentist and Bayesian approaches. Supporting Mathematica® notebooks with solutions to selected problems, additional worked examples, and a Mathematica tutorial are available at www.cambridge.org/9780521150125.

Practical Bayesian Inference

Author : Coryn A. L. Bailer-Jones
Publisher : Cambridge University Press
ISBN 13 : 1108127673
Total Pages : 306 pages
Book Rating : 4.1/5 (81 download)

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Book Synopsis Practical Bayesian Inference by : Coryn A. L. Bailer-Jones

Download or read book Practical Bayesian Inference written by Coryn A. L. Bailer-Jones and published by Cambridge University Press. This book was released on 2017-04-27 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Science is fundamentally about learning from data, and doing so in the presence of uncertainty. This volume is an introduction to the major concepts of probability and statistics, and the computational tools for analysing and interpreting data. It describes the Bayesian approach, and explains how this can be used to fit and compare models in a range of problems. Topics covered include regression, parameter estimation, model assessment, and Monte Carlo methods, as well as widely used classical methods such as regularization and hypothesis testing. The emphasis throughout is on the principles, the unifying probabilistic approach, and showing how the methods can be implemented in practice. R code (with explanations) is included and is available online, so readers can reproduce the plots and results for themselves. Aimed primarily at undergraduate and graduate students, these techniques can be applied to a wide range of data analysis problems beyond the scope of this work.

Bayesian Data Analysis for the Behavioral and Neural Sciences

Author : Todd E. Hudson
Publisher : Cambridge University Press
ISBN 13 : 9781108812900
Total Pages : 500 pages
Book Rating : 4.8/5 (129 download)

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Book Synopsis Bayesian Data Analysis for the Behavioral and Neural Sciences by : Todd E. Hudson

Download or read book Bayesian Data Analysis for the Behavioral and Neural Sciences written by Todd E. Hudson and published by Cambridge University Press. This book was released on 2021-06-30 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook bypasses the need for advanced mathematics by providing in-text computer code, allowing students to explore Bayesian data analysis without the calculus background normally considered a prerequisite for this material. Now, students can use the best methods without needing advanced mathematical techniques. This approach goes beyond "frequentist" concepts of p-values and null hypothesis testing, using the full power of modern probability theory to solve real-world problems. The book offers a fully self-contained course, which demonstrates analysis techniques throughout with worked examples crafted specifically for students in the behavioral and neural sciences. The book presents two general algorithms that help students solve the measurement and model selection (also called "hypothesis testing") problems most frequently encountered in real-world applications.

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan

Author : Franzi Korner-Nievergelt
Publisher : Academic Press
ISBN 13 : 0128016787
Total Pages : 329 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan by : Franzi Korner-Nievergelt

Download or read book Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan written by Franzi Korner-Nievergelt and published by Academic Press. This book was released on 2015-04-04 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods of conducting data analyses. The book provides the theoretical background in an easy-to-understand approach, encouraging readers to examine the processes that generated their data. Including discussions of model selection, model checking, and multi-model inference, the book also uses effect plots that allow a natural interpretation of data. Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN introduces Bayesian software, using R for the simple modes, and flexible Bayesian software (BUGS and Stan) for the more complicated ones. Guiding the ready from easy toward more complex (real) data analyses ina step-by-step manner, the book presents problems and solutions—including all R codes—that are most often applicable to other data and questions, making it an invaluable resource for analyzing a variety of data types. - Introduces Bayesian data analysis, allowing users to obtain uncertainty measurements easily for any derived parameter of interest - Written in a step-by-step approach that allows for eased understanding by non-statisticians - Includes a companion website containing R-code to help users conduct Bayesian data analyses on their own data - All example data as well as additional functions are provided in the R-package blmeco

Current Trends in Bayesian Methodology with Applications

Author : Satyanshu K. Upadhyay
Publisher : CRC Press
ISBN 13 : 1482235129
Total Pages : 674 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Current Trends in Bayesian Methodology with Applications by : Satyanshu K. Upadhyay

Download or read book Current Trends in Bayesian Methodology with Applications written by Satyanshu K. Upadhyay and published by CRC Press. This book was released on 2015-05-21 with total page 674 pages. Available in PDF, EPUB and Kindle. Book excerpt: Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics. Each chapter is self-contained and focuses on a Bayesian methodology. It gives an overview of the area, presents theoretical insights, and emphasizes applications through motivating examples. This book reflects the diversity of Bayesian analysis, from novel Bayesian methodology, such as nonignorable response and factor analysis, to state-of-the-art applications in economics, astrophysics, biomedicine, oceanography, and other areas. It guides readers in using Bayesian techniques for a range of statistical analyses.