name: hasty-hamiltonian version: 1.2.0 synopsis: Speedy traversal through parameter space. homepage: http://github.com/jtobin/hasty-hamiltonian license: MIT license-file: LICENSE author: Jared Tobin maintainer: jared@jtobin.ca category: Numeric build-type: Simple cabal-version: >=1.10 Description: Gradient-based traversal through parameter space. . This implementation of HMC algorithm uses 'lens' as a means to operate over generic indexed traversable functors, so you can expect it to work if your target function takes a list, vector, map, sequence, etc. as its argument. . If you don't want to calculate your gradients by hand you can use the handy library for automatic differentiation. . Exports a 'mcmc' function that prints a trace to stdout, as well as a 'hamiltonian' transition operator that can be used more generally. . > import Numeric.AD (grad) > import Numeric.MCMC.Hamiltonian > > target :: RealFloat a => [a] -> a > target [x0, x1] = negate ((x0 + 2 * x1 - 7) ^ 2 + (2 * x0 + x1 - 5) ^ 2) > > gTarget :: [Double] -> [Double] > gTarget = grad target > > booth :: Target [Double] > booth = Target target (Just gTarget) > > main :: IO () > main = withSystemRandom . asGenIO $ mcmc 10000 0.05 20 [0, 0] booth Source-repository head Type: git Location: http://github.com/jtobin/hasty-hamiltonian.git library default-language: Haskell2010 ghc-options: -Wall exposed-modules: Numeric.MCMC.Hamiltonian build-depends: base >= 4 && < 6 , mcmc-types >= 1.0.1 , mwc-probability >= 1.0.1 , lens >= 4 && < 5 , pipes >= 4 && < 5 , primitive >= 0.5 && < 1.0 , transformers >= 0.5 && < 1.0 Test-suite booth type: exitcode-stdio-1.0 hs-source-dirs: test main-is: Booth.hs default-language: Haskell2010 ghc-options: -rtsopts build-depends: ad >= 4 && < 5 , base >= 4 && < 6 , mwc-probability >= 1.0.1 , hasty-hamiltonian