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|
-----------------------------------------------------------------------------
-- |
-- Module : Numeric.Random
-- Copyright : (c) Alberto Ruiz 2009-14
-- License : GPL
--
-- Maintainer : Alberto Ruiz
-- Stability : provisional
--
-- Random vectors and matrices.
--
-----------------------------------------------------------------------------
module Numeric.Random (
Seed,
RandDist(..),
randomVector,
gaussianSample,
uniformSample
) where
import Numeric.GSL.Vector
import Data.Packed
import Numeric.ContainerBoot
import Numeric.LinearAlgebra.Algorithms
type Seed = Int
-- | Obtains a matrix whose rows are pseudorandom samples from a multivariate
-- Gaussian distribution.
gaussianSample :: Seed
-> Int -- ^ number of rows
-> Vector Double -- ^ mean vector
-> Matrix Double -- ^ covariance matrix
-> Matrix Double -- ^ result
gaussianSample seed n med cov = m where
c = dim med
meds = konst' 1 n `outer` med
rs = reshape c $ randomVector seed Gaussian (c * n)
m = rs `mXm` cholSH cov `add` meds
-- | Obtains a matrix whose rows are pseudorandom samples from a multivariate
-- uniform distribution.
uniformSample :: Seed
-> Int -- ^ number of rows
-> [(Double,Double)] -- ^ ranges for each column
-> Matrix Double -- ^ result
uniformSample seed n rgs = m where
(as,bs) = unzip rgs
a = fromList as
cs = zipWith subtract as bs
d = dim a
dat = toRows $ reshape n $ randomVector seed Uniform (n*d)
am = konst' 1 n `outer` a
m = fromColumns (zipWith scale cs dat) `add` am
|
