Created
October 18, 2016 08:52
-
-
Save jtobin/95573e26843cf5fa0295360d3b33d3f1 to your computer and use it in GitHub Desktop.
Revisions
-
jtobin created this gist
Oct 18, 2016 .There are no files selected for viewing
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters. Learn more about bidirectional Unicode charactersOriginal file line number Diff line number Diff line change @@ -0,0 +1,81 @@ {-# LANGUAGE DeriveFunctor #-} {-# LANGUAGE LambdaCase #-} import Control.Monad import Control.Monad.Free import qualified System.Random.MWC.Probability as MWC data ModelF r = BernoulliF Double (Bool -> r) | BetaF Double Double (Double -> r) deriving Functor type Model = Free ModelF -- terms bernoulli :: Double -> Model Bool bernoulli p = liftF (BernoulliF p id) beta :: Double -> Double -> Model Double beta a b = liftF (BetaF a b id) binomial :: Int -> Double -> Model Int binomial n p = fmap count coins where coins = replicateM n (bernoulli p) uniform :: Model Double uniform = beta 1 1 betaBinomial :: Int -> Double -> Double -> Model Int betaBinomial n a b = do p <- beta a b binomial n p -- simulation toSampler :: Model a -> MWC.Prob IO a toSampler = iterM $ \case BernoulliF p f -> MWC.bernoulli p >>= f BetaF a b f -> MWC.beta a b >>= f simulate :: Model a -> IO a simulate model = MWC.withSystemRandom . MWC.asGenIO $ MWC.sample (toSampler model) -- conditioning invert :: (Monad m, Eq b) => m a -> (a -> m b) -> [b] -> m a invert proposal model observed = loop where len = length observed loop = do parameters <- proposal generated <- replicateM len (model parameters) if generated == observed then return parameters else loop invertWithAssistance :: (Monad m, Eq c) => ([a] -> c) -> m b -> (b -> m a) -> [a] -> m b invertWithAssistance assister proposal model observed = loop where len = length observed loop = do parameters <- proposal generated <- replicateM len (model parameters) if assister generated == assister observed then return parameters else loop -- example posterior :: Model Double posterior = invert uniform bernoulli [True, True, False, True] posterior0 :: Model Double posterior0 = invertWithAssistance count uniform bernoulli obs where obs = [True, True, True, False, True, True, False, True, True, True, True, False] count :: [Bool] -> Int count = length . filter id