Painless general-purpose sampling. https://github.com/jtobin/flat-mcmc

Version on this page:1.0.1
LTS Haskell 10.3:1.5.0
Stackage Nightly 2018-01-24:1.5.0
Latest on Hackage:1.5.0

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MIT licensed by Jared Tobin
Maintained by jared@jtobin.ca

Module documentation for 1.0.1

flat-mcmc is a Haskell library for painless, efficient, general-purpose sampling from continuous distributions.

flat-mcmc uses an ensemble sampler that is invariant to affine transformations of space. It wanders a target probability distribution's parameter space as if it had been "flattened" or "unstretched" in some sense, allowing many particles to explore it locally and in parallel.

In general this sampler is useful when you want decent performance without dealing with any tuning parameters or local proposal distributions.

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.

import Numeric.MCMC.Flat
import qualified Data.Vector.Unboxed as U (unsafeIndex)

rosenbrock :: Particle -> Double
rosenbrock xs = negate (5  * (x1 - x0 ^ 2) ^ 2 + 0.05 * (1 - x0) ^ 2) where
  x0 = U.unsafeIndex xs 0
  x1 = U.unsafeIndex xs 1

origin :: Ensemble
origin = ensemble [
    particle [negate 1.0, negate 1.0]
  , particle [negate 1.0, 1.0]
  , particle [1.0, negate 1.0]
  , particle [1.0, 1.0]

main :: IO ()
main = withSystemRandom . asGenIO $ mcmc 12500 origin rosenbrock
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