Category Archives: statistics
Tukey quote I half-remembered
I was trying to remember some quote by the exploratory data analysis master John Tukey yesterday, and I think this is it: No catalog of techniques can convey a willingness to look for what can be seen, whether or not … Continue reading
Filed under statistics
Parameterizing Negative Binomial distributions
The negative binomial distribution is cool. Sometimes I think that. Sometimes I think it is more trouble than it’s worth, a complicated mess. Today, both. Wikipedia and PyMC parameterize it differently, and it is a source of continuing confusion for … Continue reading
Filed under statistics
PyMC at SciPy 2011
I just returned from the SciPy 2011 conference in Austin. Definitely a different experience than a theory conference, and definitely different than the mega-conferences I’ve found myself at lately. I think I like it. My goal was to evangelize for … Continue reading
Filed under education, global health, MCMC, statistics
Computation time and model development
20 seconds, 20 minutes, or 20 hours. These are all amounts of time that a computational method I’ve been working at some time has taken to complete processing. They each lead to a very different experience for the model developer, … Continue reading
Filed under statistics, TCS
New Stats Books
Here is a new book on Bayesian stats that Kyle forwarded on to me: Principles of Uncertainty. Chapter 11 looks unique, on “multiparty problems”, and a pdf of the whole thing is available from the book website for download.
Filed under statistics
A Slide I Like
I’m updating a talk about machine learning for verbal autopsy analysis, and I thought I’d share a slide I like. I wonder what statisticians think about this view of the world:
Filed under statistics
MCMC in Python: A simple random effects model and its extensions
A nice example of using PyMC for multilevel (aka “Random Effects”) modeling came through on the PyMC mailing list a couple of weeks ago, and I’ve put it into a git repo so that I can play around with it … Continue reading
Filed under MCMC, statistics
Journal Culture
All fields have their quirks in publication style. Today I’m thinking about statistics, because I’ve been asked to explain something about survey weights to our post-bachelor’s fellows. There is a nice paper on the matter by Andrew Gelman, which starts … Continue reading
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In the media
Jake called my attention to a recent public interest story in the NYTimes, about using the results of an on-going telephone survey on predict the demographic profile of happiest man in America. It seems like they’re making fun of simple … Continue reading
Filed under global health, statistics
MCMC in Python: Part IIb of PyMC Step Methods and their pitfalls
Two weeks ago, I slapped together a post about the banana distribution and some of my new movies sampling from it. Today I’m going to explore the performance of MCMC with the Adaptive Metropolis step method when the banana dimension … Continue reading
Filed under statistics, TCS
