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1. type Vector = V2 Float

   Rasterific	Graphics.Rasterific

   Represent a vector

2. class ArityPeano Dim v => Vector (v :: Type -> Type) a

   fixed-vector	Data.Vector.Fixed

   Type class for vectors with fixed length. Instance should provide two functions: one to create vector from N elements and another for vector deconstruction. They must obey following law:

   inspect v construct = v
   

   For example instance for 2D vectors could be written as:

   data V2 a = V2 a a
   
   type instance V2 = 2
   instance Vector V2 a where
   construct                = Fun V2
   inspect (V2 a b) (Fun f) = f a b
   

3. class ArityPeano Dim v => Vector (v :: Type -> Type) a

   fixed-vector	Data.Vector.Fixed.Cont

   Type class for vectors with fixed length. Instance should provide two functions: one to create vector from N elements and another for vector deconstruction. They must obey following law:

   inspect v construct = v
   

   For example instance for 2D vectors could be written as:

   data V2 a = V2 a a
   
   type instance V2 = 2
   instance Vector V2 a where
   construct                = Fun V2
   inspect (V2 a b) (Fun f) = f a b
   

4. module Optics.Extra.Internal.Vector

   No documentation available.

5. data Vector l m

   prometheus-client	Prometheus

   No documentation available.

6. module Data.Random.Vector

   No documentation available.

7. module Data.Array.Repa.Repr.Vector

   No documentation available.

8. module Data.TDigest.Vector

   A new data structure for accurate on-line accumulation of rank-based statistics such as quantiles and trimmed means. . See original paper: "Computing extremely accurate quantiles using t-digest" by Ted Dunning and Otmar Ertl for more details https://github.com/tdunning/t-digest/blob/master/docs/t-digest-paper/histo.pdf.

   Examples

   >>> quantile 0.99 (tdigest [1..1000] :: TDigest 25)
   Just 990.5
   

   >>> quantile 0.99 (tdigest [1..1000] :: TDigest 3)
   Just 990.3...
   

   t-Digest is more precise in tails, especially median is imprecise:

   >>> median (forceCompress $ tdigest [1..1000] :: TDigest 10)
   Just 500.5
   

   Semigroup

   This operation isn't strictly associative, but statistical variables shouldn't be affected.

   >>> let td xs = tdigest xs :: TDigest 10
   

   >>> median (td [1..500] <> (td [501..1000] <> td [1001..1500]))
   Just 750.5
   

   >>> median ((td [1..500] <> td [501..1000]) <> td [1001..1500])
   Just 750.5
   

   The linear is worst-case scenario:

   >>> let td' xs = tdigest (fairshuffle xs) :: TDigest 10
   

   >>> median (td' [1..500] <> (td' [501..1000] <> td' [1001..1500]))
   Just 750.5
   

   >>> median ((td' [1..500] <> td' [501..1000]) <> td' [1001..1500])
   Just 750.5
   

9. module VectorBuilder.Vector

   Extensions to the standard immutable Vector API.

10. module Data.Paired.Vector

    No documentation available.

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