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Comment by joeraii | Hacker News Reader

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.

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I think the question is these don't look like NormalCDF(coef/se) p-values given the coef and se you report. They tend to be too small.

From a frequentist perspective, counting zeroes don't make much sense because under the null of coef=0 there is still a chance you don't estimate coef=0, even after regularization.

    I think the question is these don't look like NormalCDF(coef/se) p-values given the coef and se you report.  They tend to be too small.

right that's my question

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

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