flat-mcmc: Painless general-purpose sampling.

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 Data.Vector (Vector, toList, fromList)

rosenbrock :: Vector Double -> Double
rosenbrock xs = negate (5  *(x1 - x0 ^ 2) ^ 2 + 0.05 * (1 - x0) ^ 2) where
  [x0, x1] = toList xs

ensemble :: Ensemble
ensemble = fromList [
    fromList [negate 1.0, negate 1.0]
  , fromList [negate 1.0, 1.0]
  , fromList [1.0, negate 1.0]
  , fromList [1.0, 1.0]
  ]

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

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• flat-mcmc-1.1.1.tar.gz [browse] (Cabal source package)
• Package description (as included in the package)

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• JaredTobin

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