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1. type Bandwidth = Double

   statistics	Statistics.Sample.KernelDensity.Simple

   The width of the convolution kernel used.

2. bandwidth :: Vector v Double => (Double -> Bandwidth) -> v Double -> Bandwidth

   statistics	Statistics.Sample.KernelDensity.Simple

   Compute the optimal bandwidth from the observed data for the given kernel. This function uses an estimate based on the standard deviation of a sample (due to Deheuvels), which performs reasonably well for unimodal distributions but leads to oversmoothing for more complex ones.

3. confidenceInterval :: Num a => Estimate ConfInt a -> (a, a)

   statistics	Statistics.Types

   Get confidence interval

4. confidenceLevel :: Num a => CL a -> a

   statistics	Statistics.Types

   Get confidence level. This function is subject to rounding errors. If 1 - CL is needed use significanceLevel instead

5. llConfidenceLevel :: LowerLimit a -> !CL Double

   statistics	Statistics.Types

   Confidence level for which limit was calculated

6. ulConfidenceLevel :: UpperLimit a -> !CL Double

   statistics	Statistics.Types

   Confidence level for which limit was calculated

7. monoidConcatMap :: (Storable a, Monoid m) => (a -> m) -> Vector a -> m

   storablevector	Data.StorableVector

   Deprecated: Use foldMap instead.

8. monoidConcatMap :: (Storable a, Monoid m) => (a -> m) -> Vector a -> m

   storablevector	Data.StorableVector.Lazy

   Deprecated: Use foldMap instead.

9. InvalidFileName :: FilePath -> FileNameError

   tar	Codec.Archive.Tar.Check

   No documentation available.

10. groupId :: Ownership -> {-# UNPACK #-} !Int

    tar	Codec.Archive.Tar.Entry

    Numeric owner group id. Should be set to 0 if unknown.

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