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Bayesian probability theory : applications in the physical sciences / Wolfgang Von Der Linden, Volker Dose and Udo Von Toussaint.

By: Contributor(s): Material type: TextTextPublication details: Cambridge : CUP, 2014.Description: xiii, 637 p. : illustrations ; 26 cmISBN:
  • 9781107035904 (hardback)
Subject(s): DDC classification:
  • 000SA.161 23 L744
Contents:
1. The meaning of probability -- 2. Basic definitions for frequentist statistics and bayesian inference-- 3. Bayesian inference -- 4. Combinatrics -- 5. Random walks -- 6. Limit theorems -- 7. Continuous distributions -- 8. The central limit theorem -- 9. Poisson processes and waiting times -- 10. Prior probabilities by transformation invariance -- 11. Testable information and maximum entropy -- 12. Qualified maximum entropy -- 13. Global smoothness -- Part III Parameter estimation-- 14. Bayesian parameter estimation -- 15. Frequentist parameter estimation -- 16. The Cramer-Rao inequality -- Part IV Testing hypotheses-- 17. The Bayesian way -- 18. The frequentist way -- 19. Sampling distributions -- 20. Comparison of Bayesian vs frequentist hypothesis tests -- Part V Eral-world applications-- 21. Regression -- 22. Consistent inference on Inconsistent data -- 23. Unrecognized signal contributions -- 24. Change point problems -- 25. Function estimation -- 26. Integral equations -- 27. Model selection -- 28. Bayesian experimental design -- Part VI Probabilistic numerical techniques-- 29. Numerical integration -- 30. Monte Carlo methods -- 31. Nested sampling-- Appendix-- References-- Index.
Summary: Covering all aspects of probability theory, statistics and data analysis from a Bayesian perspective for graduate students and researchers.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 000SA.161 L744 (Browse shelf(Opens below)) Available 135570
Total holds: 0

Includes bibliographical references (pages 620-630) and index.

1. The meaning of probability --
2. Basic definitions for frequentist statistics and bayesian inference--
3. Bayesian inference --
4. Combinatrics --
5. Random walks --
6. Limit theorems --
7. Continuous distributions --
8. The central limit theorem --
9. Poisson processes and waiting times --
10. Prior probabilities by transformation invariance --
11. Testable information and maximum entropy --
12. Qualified maximum entropy --
13. Global smoothness --

Part III Parameter estimation--
14. Bayesian parameter estimation --
15. Frequentist parameter estimation --
16. The Cramer-Rao inequality --

Part IV Testing hypotheses--
17. The Bayesian way --
18. The frequentist way --
19. Sampling distributions --
20. Comparison of Bayesian vs frequentist hypothesis tests --

Part V Eral-world applications--
21. Regression --
22. Consistent inference on Inconsistent data --
23. Unrecognized signal contributions --
24. Change point problems --
25. Function estimation --
26. Integral equations --
27. Model selection --
28. Bayesian experimental design --

Part VI Probabilistic numerical techniques--
29. Numerical integration --
30. Monte Carlo methods --
31. Nested sampling--

Appendix--
References--
Index.

Covering all aspects of probability theory, statistics and data analysis from a Bayesian perspective for graduate students and researchers.

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