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Bayesian Analysis with Python. - Second Edition

You're reading from  Bayesian Analysis with Python. - Second Edition

Product type Book
Published in Dec 2018
Publisher Packt
ISBN-13 9781789341652
Pages 356 pages
Edition 2nd Edition
Languages
Author (1):
Osvaldo Martin Osvaldo Martin
Profile icon Osvaldo Martin

Table of Contents (11) Chapters

Preface Thinking Probabilistically Programming Probabilistically Modeling with Linear Regression Generalizing Linear Models Model Comparison Mixture Models Gaussian Processes Inference Engines Where To Go Next?
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Exercises

  1. Use the grid approach with other priors; for example, try with prior = (grid <= 0.5).astype(int) or prior = abs(grid - 0.5), or try defining your own crazy priors. Experiment with other data, such as increasing the total amount of data or making it more or less even in terms of the number of heads you observe.
  2. In the code we use to estimate π, keep N fixed and re-run the code a couple of times. Notice that the results are different because we are using random numbers, but also check that the errors are more or less in the same order. Try changing the number of N points and re-run the code. Can you guesstimate how the number of N points and the error are related? For a better estimation, you may want to modify the code to compute the error as a function of N. You can also run the code a few times with the same N and compute the mean error and standard deviation...
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