hmatrix-0.7.1.0: Linear algebra and numerical computations Source code Contents Index

Data.Packed.Random Stability provisional Maintainer Alberto Ruiz <aruiz@um.es>

Description

Random vectors and matrices.

Synopsis

data RandDist = Uniform | Gaussian randomVector :: Int -> RandDist -> Int -> Vector Double gaussianSample :: Int -> Int -> Vector Double -> Matrix Double -> Matrix Double uniformSample :: Int -> Int -> [(Double, Double)] -> Matrix Double meanCov :: Matrix Double -> (Vector Double, Matrix Double)

Documentation

data RandDist Source

Constructors Uniform uniform distribution in [0,1) Gaussian normal distribution with mean zero and standard deviation one Instances Enum RandDist

randomVector Source

:: Int seed -> RandDist distribution -> Int vector size -> Vector Double Obtains a vector of pseudorandom elements from the the mt19937 generator in GSL, with a given seed. Use randomIO to get a random seed.

gaussianSample Source

:: Int seed -> Int number of rows -> Vector Double mean vector -> Matrix Double covariance matrix -> Matrix Double result Obtains a matrix whose rows are pseudorandom samples from a multivariate Gaussian distribution.

uniformSample Source

:: Int seed -> Int number of rows -> [(Double, Double)] ranges for each column -> Matrix Double result Obtains a matrix whose rows are pseudorandom samples from a multivariate uniform distribution.

meanCov :: Matrix Double -> (Vector Double, Matrix Double) Source

Compute mean vector and covariance matrix of the rows of a matrix.

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