Monthly Archives: May 2014
MCMC in Python: sampling in parallel with PyMC
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Filed under software engineering
IDV in Python: adding text callouts to a scatter plot interactively with mpld3
The thing about interactive data visualization is that its not always clear what is useful because it excites my reptile brain, and what is useful for more logical reasons. But I was asking a colleague to add some callouts to a (non-interactive) figure recently when I realized that this is a chance for interactivity to be _obviously_ useful. These finishing touches on a graphic often take me tons of time, and using a command-line plotting program just can’t be the right way to do it. How about an mpld3 plugin that lets me add text callouts interactively? And when I’m done, it can “save” the callouts, by creating the necessary Python script to generate them again? Here it is, in a notebook.
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Filed under dataviz
MCMC in Python: Estimating failure rates from observed data
A question and answer on CrossValidated, which make me reflect on the danger of knowing enough statistics to be dangerous.
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Filed under statistics
MCMC in Python: How to make a custom sampler in PyMC
The PyMC documentation is a little slim on the topic of defining a custom sampler, and I had to figure it out for some DisMod work over the years. Here is a minimal example of how I did it, in answer to a CrossValidated question.
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Filed under MCMC
MCMC in Python: How to set a custom prior with joint distribution on two parameters in PyMC
Question and answer on Stackoverflow. Motivated by question and answer on CrossValidated about modeling incidence rates.
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Filed under Uncategorized
Change Seminar: Measuring Mortality in Iraq
I gave a seminar last week for the UW computer scientists interested in doing good with technology. It’s a fun crowd. Here are the slides, requested by a regular attendee who couldn’t be there.
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Filed under global health