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Bayesian Analysis with Python

You're reading from   Bayesian Analysis with Python Introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789341652
Length 356 pages
Edition 2nd 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 (11) Chapters Close

Preface 1. Thinking Probabilistically FREE CHAPTER 2. Programming Probabilistically 3. Modeling with Linear Regression 4. Generalizing Linear Models 5. Model Comparison 6. Mixture Models 7. Gaussian Processes 8. Inference Engines 9. Where To Go Next?
10. Other Books You May Enjoy

Regression with spatial autocorrelation

The following example is taken from the book, Statistical Rethinking, by Richard McElreath. The author kindly allowed me to reuse his example here. I strongly recommend reading his book, as you will find many good examples like this and very good explanations. The only caveat is that the book examples are in R/Stan, but don't worry and keep sampling; you will find the Python/PyMC3 version of those examples in https://github.com/pymc-devs/resources.

Well, going back to the example, we have 10 different island-societies; for each one of them, we have the number of tools they use. Some theories predict that larger populations develop and sustain more tools than smaller populations. Another important factor is the contact rates among populations.

As we have number of tools as dependent variable, we can use a Poisson regression with the...

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