@hackage mighty-metropolis2.0.0
The Metropolis algorithm.
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MIT
Maintainer
jared@jtobin.ca
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Dependencies (7)
- base >=4 && <6
- kan-extensions >=5 && <6
- mcmc-types >=1.0.1
- mwc-probability >=1.0.1
- pipes >=4 && <5
- primitive >=0.6 && <1.0 Show all…
Dependents (1)
@hackage/declarative
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