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Bayesian Logical Data Analysis for t...
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Ebooks Corporation.
Bayesian Logical Data Analysis for the Physical Sciences.
紀錄類型:
書目-電子資源 : 單行本
正題名/作者:
Bayesian Logical Data Analysis for the Physical Sciences./
作者:
Gregory, Phil.
出版者:
Cambridge :Cambridge University Press, : 2005.,
面頁冊數:
488 p.
標題:
Bayesian statistical decision theory. -
電子資源:
Click here to view book
ISBN:
9780511791277 (electronic bk.)
Bayesian Logical Data Analysis for the Physical Sciences.
Gregory, Phil.
Bayesian Logical Data Analysis for the Physical Sciences.
[electronic resource]. - Cambridge :Cambridge University Press,2005. - 488 p.
Cover; Half-title; Title; Copyright; Contents; Preface; Acknowledgements; 1 Role of probability theory in science; 2 Probability theory as extended logic; 3 The how-to of Bayesian inference; 4 Assigning probabilities; 5 Frequentist statistical inference; 6 What is a statistic?; 7 Frequentist hypothesis testing; 8 Maximum entropy probabilities; 9 Bayesian inference with Gaussian errors; 10 Linear model fitting (Gaussian errors); 11 Nonlinear model fitting; 12 Markov chain Monte Carlo; 13 Bayesian revolution in spectral analysis; 14 Bayesian inference with Poisson sampling
Increasingly, researchers in many branches of science are coming into contact with Bayesian statistics or Bayesian probability theory. This book provides a clear exposition of the underlying concepts with large numbers of worked examples and problem sets. Background material is provided in appendices and supporting Mathematica notebooks are available.
Electronic reproduction.
Available via World Wide Web.
Mode of access: World Wide Web.
ISBN: 9780511791277 (electronic bk.)Subjects--Topical Terms:
96593
Bayesian statistical decision theory.
Index Terms--Genre/Form:
96803
Electronic books.
LC Class. No.: QA279.5 .G74 2005eb
Dewey Class. No.: 519.542
Bayesian Logical Data Analysis for the Physical Sciences.
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488 p.
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Cover; Half-title; Title; Copyright; Contents; Preface; Acknowledgements; 1 Role of probability theory in science; 2 Probability theory as extended logic; 3 The how-to of Bayesian inference; 4 Assigning probabilities; 5 Frequentist statistical inference; 6 What is a statistic?; 7 Frequentist hypothesis testing; 8 Maximum entropy probabilities; 9 Bayesian inference with Gaussian errors; 10 Linear model fitting (Gaussian errors); 11 Nonlinear model fitting; 12 Markov chain Monte Carlo; 13 Bayesian revolution in spectral analysis; 14 Bayesian inference with Poisson sampling
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Appendix A Singular value decompositionAppendix B Discrete Fourier Transforms; Appendix C Difference in two samples; Appendix D Poisson ON/OFF details; Appendix E Multivariate Gaussian from maximum entropy; References; Index
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Increasingly, researchers in many branches of science are coming into contact with Bayesian statistics or Bayesian probability theory. This book provides a clear exposition of the underlying concepts with large numbers of worked examples and problem sets. Background material is provided in appendices and supporting Mathematica notebooks are available.
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http://ebooks.cambridge.org/ebook.jsf?bid=CBO9780511791277
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