MIT licensed by Jared Tobin
Maintained by [email protected]
This version can be pinned in stack with:mighty-metropolis-1.2.0@sha256:b701c933b24dd6a556a57677189c1973809454c321ddf729a3f73c82234ce82a,2089

Module documentation for 1.2.0

The classic Metropolis algorithm.

Wander around parameter space according to a simple spherical Gaussian distribution.

Exports a mcmc function that prints a trace to stdout, a chain function for collecting results in-memory, and a metropolis transition operator that can be used more generally.

import Numeric.MCMC.Metropolis

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

main :: IO ()
main = withSystemRandom . asGenIO $ mcmc 10000 1 [0, 0] rosenbrock