Dense-Subset Break-the-Bank Challenge

I’m preparing for my first global travel for global health, but the net is paying attention to a paper that I think I’ll like, and I want to mention it briefly before I fly.
Computational Complexity and Information Asymmetry in Financial Products is 27 pages of serious TCS, but it is so obviously applicable that people [...]

MCMC in Python: PyMC for Bayesian Model Selection

(Updated 9/2/2009)
I never took a statistics class, so I only know the kind of statistics you learn on the street. But now that I’m in global health research, I’ve been doing a lot of on-the-job learning. This post is about something I’ve been reading about recently, how to decide if a simple statistical [...]

August is Too-Many-Projects Month

(Tap… tap… tap… is this thing on? Good.)
July was vacation month, where I went on a glorious bike tour of the Oregon/California coast, and learned definitively that I don’t like biking on the side of a highway all day. Don’t worry, I escaped in Coos Bay and took trains and buses between Eugene, [...]

Anatomy of a Django-driven Data Server

I haven’t had time to write anything this week because I am up to my neck in this Seven-Samurai-style software engineering project. You know, where a bunch of untrained villagers (that’s me) need to defend themselves against marauding bandits (that’s the Global Burden of Disease 2005 Study), so they have to learn everything about [...]

ACO in Python: Minimum Weight Perfect Matchings (a.k.a. Matching Algorithms and Reproductive Health: Part 4)

This is the final item in my series on Matching Algorithms and Reproductive Health, and it brings the story full circle, returning to the algorithms side of the show. Today I’ll demonstrate how to actually find minimum-weight perfect matchings in Python, and toss in a little story about .

Items of Interest

MIT faculty makes scholarly articles freely and openly available to the entire world.
Google Summer of Code returns, and suggested Python projects. (A nice way for students to spend the summer, especially during an “economic downturn”).
And for those of you that are looking for NSF grants to apply to: Foundations of Data and Visual Analytics.

ACO in Python: PADS for Minimum Spanning Trees

Sometimes, instead of working, I like to see what search terms are bringing readers to my blog. The most common search that healthyalgorithms has been most useless for is “minimum spanning tree python”. Today, I’ll remedy that.
But first, dear searchers, consider this: why are you searching for minimum spanning tree code in python? [...]

Hurrah for Free/Open Software like PyMC

A few posts ago, when I told you how amazingly simple it turned out to be to sample independent sets with PyMC.  Remember when I said that it was working a little differently than I expected, though?  I sent an email to the pymc-users mailing list, and, in just a few days, one of the [...]

MCMC: Running a chain, making it look easy

As I was saying in my last post, I’ve been getting interested in actually running Markov Chain Monte Carlo algorithms, instead of trying to prove things about their asymptotic performance. It seems like the “stats” way to do this is to use R and WinBUGS, but I’ve always thought that R programming looks messy. [...]