Safe Haskell	None
Language	Haskell2010

Statistics.Probability

Contents

Probability in linear space
Probability in log space. A number of operations internally cast to Log
Conversion between probability in linear and log-space.

Description

Probability-related types.

TODO instances for serialization and further stuff TODO vector instances

Synopsis

data IsNormalized
- = Normalized
- | NotNormalized
newtype Prob (n :: IsNormalized) x = Prob {
- getProb :: x
}
prob :: (Ord x, Num x, Show x) => x -> Prob Normalized x
prob' :: (Ord x, Num x, Show x) => x -> Prob NotNormalized x
newtype LogProb (n :: IsNormalized) x = LogProb {
- getLogProb :: x
}
withLog1 :: (Log x -> Log y) -> LogProb n x -> LogProb n y
withLog2 :: (Log x -> Log y -> Log z) -> LogProb n x -> LogProb n y -> LogProb n z
p2lp :: Floating x => Prob n x -> LogProb n x
lp2p :: Floating x => LogProb n x -> Prob n x
aslp :: Floating x => Iso' (Prob n x) (LogProb n x)

Documentation

data IsNormalized Source #

Constructors

Normalized
NotNormalized

Probability in linear space

newtype Prob (n :: IsNormalized) x Source #

Prob wraps a Double that encodes probabilities. If Prob is tagged as Normalized, the contained values are in the range [0,...,1], otherwise they are in the range [0,...,∞].

Constructors

Prob
Fields getProb :: x

Instances

Unbox x => Vector Vector (Prob n x) Source #
Instance details Defined in Statistics.Probability Methods basicUnsafeFreeze :: PrimMonad m => Mutable Vector (PrimState m) (Prob n x) -> m (Vector (Prob n x)) # basicUnsafeThaw :: PrimMonad m => Vector (Prob n x) -> m (Mutable Vector (PrimState m) (Prob n x)) # basicLength :: Vector (Prob n x) -> Int # basicUnsafeSlice :: Int -> Int -> Vector (Prob n x) -> Vector (Prob n x) # basicUnsafeIndexM :: Monad m => Vector (Prob n x) -> Int -> m (Prob n x) # basicUnsafeCopy :: PrimMonad m => Mutable Vector (PrimState m) (Prob n x) -> Vector (Prob n x) -> m () # elemseq :: Vector (Prob n x) -> Prob n x -> b -> b #
Unbox x => MVector MVector (Prob n x) Source #
Instance details Defined in Statistics.Probability Methods basicLength :: MVector s (Prob n x) -> Int # basicUnsafeSlice :: Int -> Int -> MVector s (Prob n x) -> MVector s (Prob n x) # basicOverlaps :: MVector s (Prob n x) -> MVector s (Prob n x) -> Bool # basicUnsafeNew :: PrimMonad m => Int -> m (MVector (PrimState m) (Prob n x)) # basicInitialize :: PrimMonad m => MVector (PrimState m) (Prob n x) -> m () # basicUnsafeReplicate :: PrimMonad m => Int -> Prob n x -> m (MVector (PrimState m) (Prob n x)) # basicUnsafeRead :: PrimMonad m => MVector (PrimState m) (Prob n x) -> Int -> m (Prob n x) # basicUnsafeWrite :: PrimMonad m => MVector (PrimState m) (Prob n x) -> Int -> Prob n x -> m () # basicClear :: PrimMonad m => MVector (PrimState m) (Prob n x) -> m () # basicSet :: PrimMonad m => MVector (PrimState m) (Prob n x) -> Prob n x -> m () # basicUnsafeCopy :: PrimMonad m => MVector (PrimState m) (Prob n x) -> MVector (PrimState m) (Prob n x) -> m () # basicUnsafeMove :: PrimMonad m => MVector (PrimState m) (Prob n x) -> MVector (PrimState m) (Prob n x) -> m () # basicUnsafeGrow :: PrimMonad m => MVector (PrimState m) (Prob n x) -> Int -> m (MVector (PrimState m) (Prob n x)) #
Enum x => Enum (Prob n x) Source #
Instance details Defined in Statistics.Probability Methods succ :: Prob n x -> Prob n x # pred :: Prob n x -> Prob n x # toEnum :: Int -> Prob n x # fromEnum :: Prob n x -> Int # enumFrom :: Prob n x -> [Prob n x] # enumFromThen :: Prob n x -> Prob n x -> [Prob n x] # enumFromTo :: Prob n x -> Prob n x -> [Prob n x] # enumFromThenTo :: Prob n x -> Prob n x -> Prob n x -> [Prob n x] #
Eq x => Eq (Prob n x) Source #
Instance details Defined in Statistics.Probability Methods (==) :: Prob n x -> Prob n x -> Bool # (/=) :: Prob n x -> Prob n x -> Bool #
Floating x => Floating (Prob n x) Source #
Instance details Defined in Statistics.Probability Methods pi :: Prob n x # exp :: Prob n x -> Prob n x # log :: Prob n x -> Prob n x # sqrt :: Prob n x -> Prob n x # (**) :: Prob n x -> Prob n x -> Prob n x # logBase :: Prob n x -> Prob n x -> Prob n x # sin :: Prob n x -> Prob n x # cos :: Prob n x -> Prob n x # tan :: Prob n x -> Prob n x # asin :: Prob n x -> Prob n x # acos :: Prob n x -> Prob n x # atan :: Prob n x -> Prob n x # sinh :: Prob n x -> Prob n x # cosh :: Prob n x -> Prob n x # tanh :: Prob n x -> Prob n x # asinh :: Prob n x -> Prob n x # acosh :: Prob n x -> Prob n x # atanh :: Prob n x -> Prob n x # log1p :: Prob n x -> Prob n x # expm1 :: Prob n x -> Prob n x # log1pexp :: Prob n x -> Prob n x # log1mexp :: Prob n x -> Prob n x #
Fractional x => Fractional (Prob n x) Source #
Instance details Defined in Statistics.Probability Methods (/) :: Prob n x -> Prob n x -> Prob n x # recip :: Prob n x -> Prob n x # fromRational :: Rational -> Prob n x #
Num x => Num (Prob n x) Source #
Instance details Defined in Statistics.Probability Methods (+) :: Prob n x -> Prob n x -> Prob n x # (-) :: Prob n x -> Prob n x -> Prob n x # (*) :: Prob n x -> Prob n x -> Prob n x # negate :: Prob n x -> Prob n x # abs :: Prob n x -> Prob n x # signum :: Prob n x -> Prob n x # fromInteger :: Integer -> Prob n x #
Ord x => Ord (Prob n x) Source #
Instance details Defined in Statistics.Probability Methods compare :: Prob n x -> Prob n x -> Ordering # (<) :: Prob n x -> Prob n x -> Bool # (<=) :: Prob n x -> Prob n x -> Bool # (>) :: Prob n x -> Prob n x -> Bool # (>=) :: Prob n x -> Prob n x -> Bool # max :: Prob n x -> Prob n x -> Prob n x # min :: Prob n x -> Prob n x -> Prob n x #
Read x => Read (Prob n x) Source #
Instance details Defined in Statistics.Probability Methods readsPrec :: Int -> ReadS (Prob n x) # readList :: ReadS [Prob n x] # readPrec :: ReadPrec (Prob n x) # readListPrec :: ReadPrec [Prob n x] #
Real x => Real (Prob n x) Source #
Instance details Defined in Statistics.Probability Methods toRational :: Prob n x -> Rational #
RealFloat x => RealFloat (Prob n x) Source #
Instance details Defined in Statistics.Probability Methods floatRadix :: Prob n x -> Integer # floatDigits :: Prob n x -> Int # floatRange :: Prob n x -> (Int, Int) # decodeFloat :: Prob n x -> (Integer, Int) # encodeFloat :: Integer -> Int -> Prob n x # exponent :: Prob n x -> Int # significand :: Prob n x -> Prob n x # scaleFloat :: Int -> Prob n x -> Prob n x # isNaN :: Prob n x -> Bool # isInfinite :: Prob n x -> Bool # isDenormalized :: Prob n x -> Bool # isNegativeZero :: Prob n x -> Bool # isIEEE :: Prob n x -> Bool # atan2 :: Prob n x -> Prob n x -> Prob n x #
RealFrac x => RealFrac (Prob n x) Source #
Instance details Defined in Statistics.Probability Methods properFraction :: Integral b => Prob n x -> (b, Prob n x) # truncate :: Integral b => Prob n x -> b # round :: Integral b => Prob n x -> b # ceiling :: Integral b => Prob n x -> b # floor :: Integral b => Prob n x -> b #
Show x => Show (Prob n x) Source #
Instance details Defined in Statistics.Probability Methods showsPrec :: Int -> Prob n x -> ShowS # show :: Prob n x -> String # showList :: [Prob n x] -> ShowS #
Unbox x => Unbox (Prob n x) Source #
Instance details Defined in Statistics.Probability
Num r => SemiRing (Prob n r) Source #
Instance details Defined in Statistics.Probability Methods srplus :: Prob n r -> Prob n r -> Prob n r Source # srmul :: Prob n r -> Prob n r -> Prob n r Source # srzero :: Prob n r Source # srone :: Prob n r Source #
data MVector s (Prob n x) Source #
Instance details Defined in Statistics.Probability data MVector s (Prob n x) = MV_Prob (MVector s x)
data Vector (Prob n x) Source #
Instance details Defined in Statistics.Probability data Vector (Prob n x) = V_Prob (Vector x)

prob :: (Ord x, Num x, Show x) => x -> Prob Normalized x Source #

Turns a value into a normalized probability. error if the value is not in the range [0,...,1].

prob' :: (Ord x, Num x, Show x) => x -> Prob NotNormalized x Source #

Simple wrapper around Prob that fixes non-normalization.

Probability in log space. A number of operations internally cast to `Log`

newtype LogProb (n :: IsNormalized) x Source #

Constructors

LogProb
Fields getLogProb :: x

Instances

Unbox x => Vector Vector (LogProb n x) Source #
Instance details Defined in Statistics.Probability Methods basicUnsafeFreeze :: PrimMonad m => Mutable Vector (PrimState m) (LogProb n x) -> m (Vector (LogProb n x)) # basicUnsafeThaw :: PrimMonad m => Vector (LogProb n x) -> m (Mutable Vector (PrimState m) (LogProb n x)) # basicLength :: Vector (LogProb n x) -> Int # basicUnsafeSlice :: Int -> Int -> Vector (LogProb n x) -> Vector (LogProb n x) # basicUnsafeIndexM :: Monad m => Vector (LogProb n x) -> Int -> m (LogProb n x) # basicUnsafeCopy :: PrimMonad m => Mutable Vector (PrimState m) (LogProb n x) -> Vector (LogProb n x) -> m () # elemseq :: Vector (LogProb n x) -> LogProb n x -> b -> b #
Unbox x => MVector MVector (LogProb n x) Source #
Instance details Defined in Statistics.Probability Methods basicLength :: MVector s (LogProb n x) -> Int # basicUnsafeSlice :: Int -> Int -> MVector s (LogProb n x) -> MVector s (LogProb n x) # basicOverlaps :: MVector s (LogProb n x) -> MVector s (LogProb n x) -> Bool # basicUnsafeNew :: PrimMonad m => Int -> m (MVector (PrimState m) (LogProb n x)) # basicInitialize :: PrimMonad m => MVector (PrimState m) (LogProb n x) -> m () # basicUnsafeReplicate :: PrimMonad m => Int -> LogProb n x -> m (MVector (PrimState m) (LogProb n x)) # basicUnsafeRead :: PrimMonad m => MVector (PrimState m) (LogProb n x) -> Int -> m (LogProb n x) # basicUnsafeWrite :: PrimMonad m => MVector (PrimState m) (LogProb n x) -> Int -> LogProb n x -> m () # basicClear :: PrimMonad m => MVector (PrimState m) (LogProb n x) -> m () # basicSet :: PrimMonad m => MVector (PrimState m) (LogProb n x) -> LogProb n x -> m () # basicUnsafeCopy :: PrimMonad m => MVector (PrimState m) (LogProb n x) -> MVector (PrimState m) (LogProb n x) -> m () # basicUnsafeMove :: PrimMonad m => MVector (PrimState m) (LogProb n x) -> MVector (PrimState m) (LogProb n x) -> m () # basicUnsafeGrow :: PrimMonad m => MVector (PrimState m) (LogProb n x) -> Int -> m (MVector (PrimState m) (LogProb n x)) #
Eq x => Eq (LogProb n x) Source #
Instance details Defined in Statistics.Probability Methods (==) :: LogProb n x -> LogProb n x -> Bool # (/=) :: LogProb n x -> LogProb n x -> Bool #
(Precise x, RealFloat x) => Num (LogProb n x) Source #
Instance details Defined in Statistics.Probability Methods (+) :: LogProb n x -> LogProb n x -> LogProb n x # (-) :: LogProb n x -> LogProb n x -> LogProb n x # (*) :: LogProb n x -> LogProb n x -> LogProb n x # negate :: LogProb n x -> LogProb n x # abs :: LogProb n x -> LogProb n x # signum :: LogProb n x -> LogProb n x # fromInteger :: Integer -> LogProb n x #
Ord x => Ord (LogProb n x) Source #
Instance details Defined in Statistics.Probability Methods compare :: LogProb n x -> LogProb n x -> Ordering # (<) :: LogProb n x -> LogProb n x -> Bool # (<=) :: LogProb n x -> LogProb n x -> Bool # (>) :: LogProb n x -> LogProb n x -> Bool # (>=) :: LogProb n x -> LogProb n x -> Bool # max :: LogProb n x -> LogProb n x -> LogProb n x # min :: LogProb n x -> LogProb n x -> LogProb n x #
Show x => Show (LogProb n x) Source #
Instance details Defined in Statistics.Probability Methods showsPrec :: Int -> LogProb n x -> ShowS # show :: LogProb n x -> String # showList :: [LogProb n x] -> ShowS #
Unbox x => Unbox (LogProb n x) Source #
Instance details Defined in Statistics.Probability
(Num d, Fractional d) => NumericLimits (LogProb n d) Source #
Instance details Defined in Statistics.Probability Methods minFinite :: LogProb n d Source # maxFinite :: LogProb n d Source #
data MVector s (LogProb n x) Source #
Instance details Defined in Statistics.Probability data MVector s (LogProb n x) = MV_LogProb (MVector s x)
data Vector (LogProb n x) Source #
Instance details Defined in Statistics.Probability data Vector (LogProb n x) = V_LogProb (Vector x)

withLog1 :: (Log x -> Log y) -> LogProb n x -> LogProb n y Source #

withLog2 :: (Log x -> Log y -> Log z) -> LogProb n x -> LogProb n y -> LogProb n z Source #

Conversion between probability in linear and log-space.

p2lp :: Floating x => Prob n x -> LogProb n x Source #

Turn probability into log-probability.

lp2p :: Floating x => LogProb n x -> Prob n x Source #

Turn log-probability into probability.

aslp :: Floating x => Iso' (Prob n x) (LogProb n x) Source #

An isomorphism between Prob and LogProb.

Documentation

Probability in linear space

Probability in log space. A number of operations internally cast to Log

Conversion between probability in linear and log-space.

Probability in log space. A number of operations internally cast to `Log`