Bayesian logistic regression software

Aleks pointed me to this site by Alexander Genkin, David D. Lewis, and David Madigan that has a program for Bayesian logistic regression. It appears to allow some hierarchical modeling and can fit very large datasets. I haven’t tried it out yet but it looks pretty cool. I imagine that for some complicated problems (for example, estimating state-by-state time series of public opinion), it probably wouldn’t work “straight out of the box”–but that’s fine, nothing else is available to solve these problems. The good news is that the program of Genkin, Lewis, and Madigan is open-source and (apparently) fast, so it could be possible and worth it to go inside and adapt its code as necessary to fit more complicated multilevel models.

P.S. Here’s the paper. According to Yu-Sung, they use a one-variable-at-a-time update, so maybe some rotation would speed things up.

3 thoughts on “Bayesian logistic regression software

  1. Boris,

    I know what you're saying, but the flip side is that R chokes on large datasets, so it actually be an advantage that this package does not run from R.

  2. It seems that the data file format requires all features for a particular case to be on the same line. I'd like to use this software on 20 cases with 50,000 features, but I don't have a spreadsheet that has enough columns for 50,000 features (plus another 50,000 columns for the feature IDs).

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