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Bayesian Inference

Bayesian Inference


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About the Book

Knowledge an Logic.- Bayes' Theorem.- Probable and Improbable Data.- Descriptions of Distributions I: Real x.- Description of Distributions II: Natural x.- Form Invariance I.- Examples of Invariant Measures.- A Linear Representation of Form Invariance.- Going Beyond Form Invariance: The Geometric Prior.- Inferring the Mean or Standard Deviation.- Form Invariance II: Natural x.- Item Response Theory.- On the Art of Fitting .- Problems and Solutions.- Description of Distributions I.- Real x.- Form Invariance I.- Beyond Form Invariance: The Geometric Prior.- Inferring Mean or Standard Deviation.- Form Invariance II: Natural x.- Item Response Theory.- On the Art of Fitting.
About the Author: Hanns Ludwig Harney, born in 1939, professor at the University of Heidelberg. He has contributed to experimental and theoretical physics within the Max-Planck Institute for Nuclear Physics at Heidelberg. His interest is focused on symmetries, such as isospin and its violation, as well as chaos, observed as reproducible fluctuations. Since the 1990's, the symmetry properties of common probability distributions lead him to a reformulation of Bayesian inference.


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Product Details
  • ISBN-13: 9783319824031
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Height: 234 mm
  • No of Pages: 243
  • Spine Width: 14 mm
  • Weight: 417 gr
  • ISBN-10: 3319824031
  • Publisher Date: 23 Jun 2018
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Sub Title: Data Evaluation and Decisions
  • Width: 156 mm


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