abstract: Sampling from a large discrete distribution is a common problem in statistics. In this talk, we'll consider a real-world situation where the properties of the distribution cause common approaches to break down, and we'll arrive at a Haskell-based solution that fixes the problem.
bio: Chad Scherrer works in the Computational Mathematics group at Pacific Northwest National Laboratory. His research interests include computational statistics, Bayesian modeling, and functional programming.
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