Wolfram Library Archive

Courseware Demos MathSource Technical Notes
All Collections Articles Books Conference Proceedings

Bayesian Logical Data Analysis for the Physical Sciences: A Comparative Approach with Mathematica Support

Phil Gregory
Organization: University of British Columbia
Book information

Publisher: Cambridge University Press (Cambridge, UK)
Copyright year: 2010
ISBN: 052184150X
Medium: Hardcover
Pages: 486
Out of print?: N
Buy this book
Book cover image

Role of Probability Theory in Science | Probability Theory as Extended Logic | The How-To of Bayesian Inference | Assigning Probabilities | Frequentist Statistical Inference | What Is a Statistic? | Frequentist Hypothesis Testing | Maximum Entropy Probabilities | Bayesian Inference with Gaussian Errors | Linear Model Fitting (Gaussian Errors) | Nonlinear Model Fitting | Markov Chain Monte Carlo | Bayesian Revolution in Spectral Analysis | Bayesian Inference with Poisson Sampling | Appendix A: Singular Value Decomposition | Appendix B: Discrete Fourier Transforms | Appendix C: Difference in Two Samples | Appendix D: Poisson ON/OFF Details | Appendix E: Multivariate Gaussian from Maximum Entropy

This book provides a clear exposition of the underlying concepts of Bayesian analysis, with large numbers of worked examples and problem sets. It also discusses numerical techniques for implementing the Bayesian calculations, including an introduction to Markov chain Monte Carlo integration and linear and nonlinear least-squares analysis seen from a Bayesian perspective.

Background material is provided in appendices, and supporting Mathematica notebooks are available from the publisher, providing an easy learning route for upper-undergraduates, graduate students, or any serious researcher in physical sciences or engineering.

*Mathematics > Probability and Statistics

probability, statistics, logic, Bayesian, frequentist, statistical inference, hypothesis testing, maximum entropy, Poisson sampling, ARMA, apodizing function, APT MCMC, ACF, autoregressive, Bayes, Behrens-Fisher, Blackman-Tukey, CDF, Chi square, convolution, DFT, Erlang distribution, ESD, Gregory-Loredo method, Jeffreys prior, Kolmogorov-Smirnov test, Kullback entropy, Lebesque measure, leptokurtic distribution, Levenberg-Marquardt method, Lomb-Scargle periodogram, Markov chain, MCMC, Metropolis-Hastings, MPM, Nyquist frequency, PSD, Schuster periodogram, Shannon-Jaynes entropy, Weiner filter, Yule-Walker equations