Bayesian Logical Data Analysis for the Physical Sciences: A Comparative Approach with Mathematica« Support (Google eBook)
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.
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Bayesian Reasoning in Data Analysis: A Critical Introduction
No preview available - 2003
Probability theory as extended logic
The howto of Bayesian inference
Frequentist statistical inference
What is a statistic?
Frequentist hypothesis testing
Maximum entropy probabilities
Nonlinear model fitting
Markov chain Monte Carlo
l3 Bayesian revolution in spectral analysis
Bayesian inference with Poisson sampling
Appendix A Singular value decomposition
Difference in two samples
Poisson ONOFF details
Bayesian inference with Gaussian errors
Linear model fitting Gaussian errors
Bayesian Logical Data Analysis for the Physical Sciences by Phil ...
Extracted from:. Bayesian Logical Data Analysis for the Physical Sciences. by Phil Gregory. Preface. The goal of science is to unlock nature's secrets. ...
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pc Gregory. Bayesian Logical Data Analysis for the Physical Sciences. Abril 2005, Cambridge University Press. Increasingly, researchers in many branches of ...
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Bayesian logical data analysis for the physical sciences; a ...
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From: mollwollfumble «, 7/09/2005 9:21:15 AM. Subject: Statistics, post id: 1816989. I've been wanting to get a good statistics book for some time and have ...
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University of Chicago Press - Bayesian Analysis of Data for HD ...
Gregory, pc 2005, Bayesian Logical Data Analysis for the Physical Sciences: A Comparative Approach with Mathematica Support (Cambridge: Cambridge Univ. ...
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SAMSI Astrostatistics Tutorial. More Markov chain Monte Carlo. &. Demo of Mathematica software. Phil Gregory. University of British Columbia ...
astrostatistics.psu.edu/ samsi06/ tutorials/ tut1gregoryl3.pdf
Phys. Rev. D 73, 123524 (2006): Pahud et al. - Model selection ...
Model selection forecasts for the spectral index from the Planck satellite. C├ędric Pahud, Andrew R. Liddle, Pia Mukherjee, and David Parkinson ...
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Bayesian Logical Data Analysis for the Physical Sciences
Bayesian Logical Data Analysis for the Physical Sciences. Bayesian Logical Data Analysis for the Physical Sciences. Purchase this Book · Purchase this Book ...
รายละเอียด :. Increasingly, researchers in many branches of science are coming into contact with Bayesian statistics or Bayesian probability theory. ...
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