# Tag Archives: MCMC

## MCMC in Python: sim and fit with same model

Here is a github issue and solution that I saw the other day. I think it’s a nice pattern.

```def generate_model(values={'mu': true_param, 'm': None}):

#prior
mu = pymc.Uniform("mu", lower=-10, upper=10, value=values['mu'],
observed=(values['mu'] is not None))

# likelihood function
m = pymc.Normal("m", mu=mu, tau=tau, value=values['m'],
observed=(values['m'] is not None))

return locals()
```

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## MCMC in Python: Fit a non-linear function with PyMC

Here is a recent q&a on stack overflow that I did and liked.

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## The one before that

Jake Vanderplas’s comparison of Python MCMC modules was preceded by a Bayesian polemic. In general, I find the stats philosophy war old-timey and distracting, but his comparison of confidence intervals and credible intervals is something I need to understand better.

http://jakevdp.github.io/blog/2014/06/12/frequentism-and-bayesianism-3-confidence-credibility/

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## MCMC in Python: a bake-off

While I’m on a microblogging spree, I’ve been meaning to link to this informative comparison of pymc, emcee, and pystan: http://jakevdp.github.io/blog/2014/06/14/frequentism-and-bayesianism-4-bayesian-in-python/

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## MCMC in Python: Another thing that turns out to be hard

Here is an interesting StackOverflow question, about a model for data distributed as the sum of two uniforms with unknown support. I was surprised how hard it was for me.

http://stackoverflow.com/questions/24379868/estimate-the-parameters-of-a-random-variable-which-is-the-sum-of-uniform-random/24397044#24397044

I think the future of probabilistic programming should be to make a model for this easy to code.

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## MCMC in Python: Never… no… always check for convergence

I’ve had no teaching responsibilities over the last quarter, and I must miss it. I’ve found myself responding to PyMC questions on StackOverflow more than ever before. It is an interesting window into what is hard in Bayesian computation. Checking (and achieving) MCMC convergence is one thing that is hard. Here are some questions and answers that include it:

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## MCMC in Python: sampling in parallel with PyMC

Question and answer on Stack Overflow.

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