Painless, efficient, general-purpose sampling from continuous distributions.
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commit 401d340e363d1d11f57bf83bcd0a651628742a81
parent ec363267692af734c9c3086c780a5af16e200d1e
Author: Jared Tobin <jared@jtobin.ca>
Date:   Sun,  3 Apr 2016 20:19:35 +0700

More README stuff.

MREADME.md | 6+++---
1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md @@ -12,9 +12,9 @@ In general this sampler is useful when you want decent performance without dealing with any tuning parameters or local proposal distributions. Check out the paper describing the algorithm [here](http://msp.org/camcos/2010/5-1/camcos-v5-n1-p04-p.pdf), and a paper on -some potential limitations [here](http://arxiv.org/abs/1509.02230). - -http://arxiv.org/abs/1509.02230 +some potential limitations [here](http://arxiv.org/abs/1509.02230). There is +also also a robust Python implementation +[here](http://dan.iel.fm/emcee/current/). *flat-mcmc* exports an 'mcmc' function that prints a trace to stdout, as well as a 'flat' transition operator that can be used more generally.