The flat-mcmc package
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
|Versions||0.1.0.0, 1.0.0, 1.0.1|
|Dependencies||base (<5), mcmc-types (>=1.0.1 && <2), monad-par, monad-par-extras, mwc-probability (>=1.0.1 && <2), pipes (==4.*), primitive, transformers, vector [details]|
|Source repository||head: git clone http://github.com/jtobin/flat-mcmc.git|
|Uploaded||Wed Apr 6 13:42:23 UTC 2016 by JaredTobin|
|Distributions||LTSHaskell:1.0.1, NixOS:1.0.1, Stackage:1.0.1|
|Downloads||355 total (13 in the last 30 days)|
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