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Bayesian Analysis with Python

You're reading from   Bayesian Analysis with Python Unleash the power and flexibility of the Bayesian framework

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Product type Paperback
Published in Nov 2016
Publisher Packt
ISBN-13 9781785883804
Length 282 pages
Edition 1st Edition
Languages
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Author (1):
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Osvaldo Martin Osvaldo Martin
Author Profile Icon Osvaldo Martin
Osvaldo Martin
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Table of Contents (10) Chapters Close

Preface 1. Thinking Probabilistically - A Bayesian Inference Primer FREE CHAPTER 2. Programming Probabilistically – A PyMC3 Primer 3. Juggling with Multi-Parametric and Hierarchical Models 4. Understanding and Predicting Data with Linear Regression Models 5. Classifying Outcomes with Logistic Regression 6. Model Comparison 7. Mixture Models 8. Gaussian Processes Index

Index

A

  • ANalysis Of VAriance (ANOVA)
    • about / Generalized linear models
  • automatic differentiation variational inference (ADVI) / Variational methods

B

  • bandwidth
    • about / The Gaussian kernel
  • Bayes factors
    • about / Bayes factors
    • analogy, with information criteria / Analogy with information criteria
    • computing / Computing Bayes factors
    • common problems, when computing / Common problems computing Bayes factors
    • and information criteria / Bayes factors and information criteria
  • Bayesian analysis
    • communicating / Communicating a Bayesian analysis
  • Bayesian information criterion (BIC) / Bayesian information criterion
  • Bayesian maximum a posteriori (MAP) estimation / Akaike information criterion
  • Bayes theorem
    • and statistical inference / Bayes' theorem and statistical inference
  • beta-binomial
    • about / Beta-binomial and negative binomial

C

  • central limit theorem (CLT)
    • about /...
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