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module Probability.Distribution.Normal where
import Probability.Random
import MCMC
foreign import bpcall "Distribution:" normal_density :: Double -> Double -> Double -> LogDouble
foreign import bpcall "Distribution:" normal_cdf :: Double -> Double -> Double -> Double
foreign import bpcall "Distribution:" normal_quantile :: Double -> Double -> Double -> Double
foreign import bpcall "Distribution:" sample_normal :: Double -> Double -> IO Double
data Normal = Normal Double Double
instance Dist Normal where
type Result Normal = Double
dist_name _ = "Normal"
instance IOSampleable Normal where
sampleIO (Normal mu sigma) = sample_normal mu sigma
instance HasPdf Normal where
pdf (Normal mu sigma) x = normal_density mu sigma x
instance Dist1D Normal where
cdf (Normal mu sigma) x = normal_cdf mu sigma x
instance ContDist1D Normal where
quantile (Normal mu sigma) p = normal_quantile mu sigma p
instance MaybeMean Normal where
maybeMean (Normal mu _) = Just mu
instance Mean Normal
instance MaybeVariance Normal where
maybeStdDev (Normal _ sigma) = Just $ sigma
instance Variance Normal
instance HasAnnotatedPdf Normal where
annotated_densities dist@(Normal mu sigma) x = do
in_edge "mu" mu
in_edge "sigma" sigma
return ([pdf dist x], ())
{-
So, to sample something for MCMC we need
- pure sampling routine.
+ MCMC-specific:
- effect
- (dist_name dist)
- annotated_densities dist
OR
- sampling routine made up of other sampling actions.
-}
instance Sampleable Normal where
sample dist@(Normal mu sigma) = RanDistribution2 dist normal_effect
normal_bounds = realLine
normal_effect x = add_move $ sliceSample x normal_bounds
normal mu sigma = Normal mu sigma
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