Copyright	(c) Matthew Donadio 2003
License	GPL
Maintainer	m.p.donadio@ieee.org
Stability	experimental
Portability	portable
Safe Haskell	Safe
Language	Haskell98

Numeric.Random.Distribution.Normal

Description

Module for transforming a list of uniform random variables into a list of normal random variables.

Synopsis

normal_clt :: Int -> (Double, Double) -> [Double] -> [Double]
normal_bm :: (Double, Double) -> [Double] -> [Double]
normal_ar :: (Double, Double) -> [Double] -> [Double]
normal_r :: (Double, Double) -> [Double] -> [Double]

Documentation

normal_clt Source #

Arguments

:: Int	Number of uniforms to sum
-> (Double, Double)	(mu,sigma)
-> [Double]	U
-> [Double]	X

Normal random variables via the Central Limit Theorm (not explicity given, but see Ross)

If mu=0 and sigma=1, then this will generate numbers in the range [-n2,n2]

normal_bm Source #

Arguments

:: (Double, Double)	(mu,sigma)
-> [Double]	U
-> [Double]	X

Normal random variables via the Box-Mueller Polar Method (Ross, pp 450--452)

If mu=0 and sigma=1, then this will generate numbers in the range [-8.57,8.57] assuing that the uniform RNG is really giving full precision for doubles.

normal_ar Source #

Arguments

:: (Double, Double)	(mu,sigma)
-> [Double]	U
-> [Double]	X

Acceptance-Rejection Method (Ross, pp 448--450)

If mu=0 and sigma=1, then this will generate numbers in the range [-36.74,36.74] assuming that the uniform RNG is really giving full precision for doubles.

normal_r Source #

Arguments

:: (Double, Double)	(mu,sigma)
-> [Double]	U
-> [Double]	X

Ratio Method (Kinderman-Monahan) (Knuth, v2, 2ed, pp 125--127)

If mu=0 and sigma=1, then this will generate numbers in the range -1e15,1e15 assuming that the uniform RNG is really giving full precision for doubles.