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Author: Joseph M. Hilbe Publisher: Cambridge University Press ISBN: 1108210740 Category : Mathematics Languages : en Pages : 429
Book Description
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.
Author: Joseph M. Hilbe Publisher: Cambridge University Press ISBN: 1108210740 Category : Mathematics Languages : en Pages : 429
Book Description
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.
Author: Michael P. Hobson Publisher: Cambridge University Press ISBN: 0521887941 Category : Mathematics Languages : en Pages : 317
Book Description
Comprehensive introduction to Bayesian methods in cosmological studies, for graduate students and researchers in cosmology, astrophysics and applied statistics.
Author: Joseph M. Hilbe Publisher: Cambridge University Press ISBN: 1107028337 Category : Business & Economics Languages : en Pages : 301
Book Description
This book provides guidelines and fully worked examples of how to select, construct, interpret and evaluate the full range of count models.
Author: Andrés Asensio Ramos Publisher: Cambridge University Press ISBN: 1107102138 Category : Mathematics Languages : en Pages : 209
Book Description
Provides an overview of the fundamentals of Bayesian inference and its applications within astrophysics, for graduate students and researchers.
Author: Graham W. Griffiths Publisher: Cambridge University Press ISBN: 131665415X Category : Mathematics Languages : en Pages : 637
Book Description
This book presents the latest numerical solutions to initial value problems and boundary value problems described by ODEs and PDEs. The author offers practical methods that can be adapted to solve wide ranges of problems and illustrates them in the increasingly popular open source computer language R, allowing integration with more statistically based methods. The book begins with standard techniques, followed by an overview of 'high resolution' flux limiters and WENO to solve problems with solutions exhibiting high gradient phenomena. Meshless methods using radial basis functions are then discussed in the context of scattered data interpolation and the solution of PDEs on irregular grids. Three detailed case studies demonstrate how numerical methods can be used to tackle very different complex problems. With its focus on practical solutions to real-world problems, this book will be useful to students and practitioners in all areas of science and engineering, especially those using R.
Author: Phil Gregory Publisher: Cambridge University Press ISBN: 113944428X Category : Mathematics Languages : en Pages : 498
Book Description
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.
Author: Gutti Jogesh Babu Publisher: CRC Press ISBN: 9780412983917 Category : Mathematics Languages : en Pages : 242
Book Description
Modern astronomers encounter a vast range of challenging statistical problems, yet few are familiar with the wealth of techniques developed by statisticians. Conversely, few statisticians deal with the compelling problems confronted in astronomy. Astrostatistics bridges this gap. Authored by a statistician-astronomer team, it provides professionals and advanced students in both fields with exposure to issues of mutual interest. In the first half of the book the authors introduce statisticians to stellar, galactic, and cosmological astronomy and discuss the complex character of astronomical data. For astronomers, they introduce the statistical principles of nonparametrics, multivariate analysis, time series analysis, density estimation, and resampling methods. The second half of the book is organized by statistical topic. Each chapter contains examples of problems encountered astronomical research and highlights methodological issues. The final chapter explores some controversial issues in astronomy that have a strong statistical component. The authors provide an extensive bibliography and references to software for implementing statistical methods. The "marriage" of astronomy and statistics is a natural one and benefits both disciplines. Astronomers need the tools and methods of statistics to interpret the vast amount of data they generate, and the issues related to astronomical data pose intriguing challenges for statisticians. Astrostatistics paves the way to improved statistical analysis of astronomical data and provides a common ground for future collaboration between the two fields.
Author: Vicent J. Martinez Publisher: CRC Press ISBN: 1420036165 Category : Mathematics Languages : en Pages : 451
Book Description
Over the last decade, statisticians have developed new statistical tools in the field of spatial point processes. At the same time, observational efforts have yielded a huge amount of new cosmological data to analyze. Although the main tools in astronomy for comparing theoretical results with observation are statistical, in recent years, cosmologis
Author: Eric D. Feigelson Publisher: Springer Science & Business Media ISBN: 146143520X Category : Mathematics Languages : en Pages : 544
Book Description
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.
Author: Joseph M. Hilbe
Author: Joseph M. Hilbe
Author: Michael P. Hobson
Author: Joseph M. Hilbe
Author: Eric D. Feigelson
Author: Andrés Asensio Ramos
Author: Graham W. Griffiths
Author: Phil Gregory
Author: Gutti Jogesh Babu
Author: Vicent J. Martinez
Author: Eric D. Feigelson