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Within LTS Haskell 24.45 (ghc-9.10.3)

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1. uniformB :: UniformDistribution -> Double

   statistics	Statistics.Distribution.Uniform

   Upper boundary of distribution

2. uniformDistr :: Double -> Double -> UniformDistribution

   statistics	Statistics.Distribution.Uniform

   Create uniform distribution.

3. uniformDistrE :: Double -> Double -> Maybe UniformDistribution

   statistics	Statistics.Distribution.Uniform

   Create uniform distribution.

4. rfor :: Monad m => Int -> Int -> (Int -> m ()) -> m ()

   statistics	Statistics.Function

   Simple reverse-for loop. Counts from start-1 to end (which must be less than start).

5. welfordMean :: Vector v Double => v Double -> Double

   statistics	Statistics.Sample

   O(n) Arithmetic mean. This uses Welford's algorithm to provide numerical stability, using a single pass over the sample data. Compared to mean, this loses a surprising amount of precision unless the inputs are very large.

6. module Statistics.Transform

   Fourier-related transformations of mathematical functions. These functions are written for simplicity and correctness, not speed. If you need a fast FFT implementation for your application, you should strongly consider using a library of FFTW bindings instead.

7. fromForeignPtr :: ForeignPtr a -> Int -> Vector a

   storablevector	Data.StorableVector.Base

   O(1) Build a Vector from a ForeignPtr

8. inlinePerformIO :: IO a -> a

   storablevector	Data.StorableVector.Base

   Just like Unsafe.performIO, but we inline it. Big performance gains as it exposes lots of things to further inlining. Very unsafe. In particular, you should do no memory allocation inside an inlinePerformIO block. On Hugs this is just Unsafe.performIO.

9. toForeignPtr :: Vector a -> (ForeignPtr a, Int, Int)

   storablevector	Data.StorableVector.Base

   O(1) Deconstruct a ForeignPtr from a Vector

10. NotTarFormat :: FormatError

    tar	Codec.Archive.Tar

    No documentation available.

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