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module Probability.Dist (module Probability.Dist,
module Numeric.LogDouble
) where
import Numeric.LogDouble
import Data.Maybe (fromJust)
class Dist d where
type Result d
dist_name :: d -> String
dist_name _ = "unnamed"
-- We can sample from these directly/atomically.
class Dist d => IOSampleable d where
sampleIO :: d -> IO (Result d)
-- We can compute the density/probability for these.
class Dist d => HasPdf d where
pdf :: d -> Result d -> LogDouble
class Dist d => Dist1D d where
cdf :: d -> Double -> Double
upper_bound :: d -> Maybe (Result d)
lower_bound :: d -> Maybe (Result d)
upper_bound _ = Nothing
lower_bound _ = Nothing
bounds d = (lower_bound d, upper_bound d)
class (Dist d, Result d ~ Double) => ContDist1D d where
quantile :: d -> Double -> Double
class Dist1D d => MaybeMean d where
maybeMean :: d -> Maybe Double
class MaybeMean d => Mean d where
mean :: d -> Double
mean = fromJust . maybeMean
class MaybeMean d => MaybeVariance d where
maybeVariance :: d -> Maybe Double
maybeStdDev :: d -> Maybe Double
maybeVariance = fmap (\x -> x * x) . maybeStdDev
maybeStdDev = fmap sqrt . maybeVariance
class MaybeVariance d => Variance d where
variance :: d -> Double
stdDev :: d -> Double
variance = fromJust . maybeVariance
stdDev = fromJust . maybeStdDev
|
