Here is a StackOverflow question with a nice figure:

Is there a nice, simple reference for just what exactly these graphical model figures mean? I want more of them.

Here is a StackOverflow question with a nice figure:

Is there a nice, simple reference for just what exactly these graphical model figures mean? I want more of them.

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I like answering PyMC questions on Stack Overflow, but sometimes I give an answer and end up the one with the question. Like what would you model as the sum of a Poisson and a Negative Binomial?

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

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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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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.

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

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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:

http://stackoverflow.com/questions/24294203/difference-between-bugs-model-and-pymc/24347102#24347102

http://stackoverflow.com/questions/24242660/pymc3-multiple-observed-values/24271760#24271760

http://stackoverflow.com/questions/24402834/fitting-power-law-function-with-pymc/24413323#24413323

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