joeraii

interesting yeah some of them definitely don't look right. the output is from scipy's stats.ttest_1samp

We spent a little time modeling various transforms of absolute score. The top features are essentially the same, but the coefficient variance is a lot higher. We're also interested in modeling rank or mindshare "stickiness" -- some articles remain in higher spots longer than others.

to be honest we just recorded the coeff values for each replicate and did the bootstrap variance calculation.

% of replicates with (coef==0) is potentially much more clever, especially since that's the test we want to perform anyway. i'll run that over the data and see what changes.

yeah pretty strong l1--most features were 0. we binarized rank on I_{rank<=20}. it turns out there are tons of articles beyond the first page that stay low forever. check out the interactive viz vad made: http://hn.metamx.com (warning 2.6MB compressed js ahead)

actually, we were serving the blog off of a tiny, poorly configured apache instance :)