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module Statistics.Distribution.
Uniform Variate distributed uniformly in the interval.
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statistics Statistics.Distribution.Uniform Uniform distribution from A to B
uniformA :: UniformDistribution -> Doublestatistics Statistics.Distribution.Uniform Low boundary of distribution
uniformB :: UniformDistribution -> Doublestatistics Statistics.Distribution.Uniform Upper boundary of distribution
uniformDistr :: Double -> Double -> UniformDistributionstatistics Statistics.Distribution.Uniform Create uniform distribution.
uniformDistrE :: Double -> Double -> Maybe UniformDistributionstatistics Statistics.Distribution.Uniform Create uniform distribution.
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).
welfordMean :: Vector v Double => v Double -> Doublestatistics 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.
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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.
fromForeignPtr :: ForeignPtr a -> Int -> Vector astorablevector Data.StorableVector.Base O(1) Build a Vector from a ForeignPtr