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

:: 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

:: (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

:: (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

:: (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.

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