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Bayesian Inference : Parameter Estimation and Decisions /

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The book provides a generalization of Gaussian error intervals to situations where the data follow non-Gaussian distributions. This usually occurs in frontier science, where the observed parameter is just above background or the histogram of multiparametric data contains empty bins. Then the validit...

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Bibliographic Details
Main Author: Harney, Hanns L.
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2003.
Series:Advanced texts in physics.
Subjects:
Physics.
Computer science > Mathematics.
Quantum theory.
Mathematical statistics.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Knowledge and Logic
  • Bayes' Theorem
  • Probable and improbable Data
  • Bayes' Theorem and the Truth
  • Description of Distributions I: Probability Densities
  • Description of Distributions II: Form Invariance I: Real x
  • Examples of Invariant Measures
  • A Linear Representation of Form Invariance
  • Beyond Form Invariance: The Geometric Prior
  • Econophysics
  • Inferring Mean or Standard Deviation
  • Form Invariance II: Natural x
  • Independence of Parameters
  • The Art of Fitting I: Real x
  • Judging a Fit I: Real x
  • The Art of Fitting II: Natural x
  • Judging a Fit II: Natural x
  • Summary
  • A Problems
  • B Form Invariance I: Probability Densities
  • C Beyond Form Invariance: The Geometric Prior
  • D Inferring Mean or Standard Deviation
  • E Form Invariance II: Natural x
  • F Independence of Parameters
  • G The Art of Fitting I: Real x
  • H Judging a Fit II: Natural x
  • Bibliography.