Examples of umontreal.iro.lecuyer.randvar.NormalGen

• umontreal.iro.lecuyer.randvar.NormalGen
  This class implements methods for generating random variates from the normal distribution N(μ, σ). It has mean μ and variance σ², where σ > 0. Its density function is

  f (x) = 1/(2π)^1/2σe^{(x-μ)2/(2σ2)}

  The nextDouble method simply calls inverseF on the distribution.

  The following table gives the CPU time needed to generate 10⁸ standard normal random variates using the different implementations available in SSJ. The first time is for a generator object (non-static method), and the second time is for the static method where no object is created. These tests were made on a machine with processor AMD Athlon 4000, running Red Hat Linux, with clock speed at 2403 MHz. The static method nextDouble() for NormalBoxMullerGen and NormalPolarGen uses only one number out of two that are generated; thus they are twice slower than the non-static method.

  Generator	time in seconds	time in seconds
  	(object)	(static)
  NormalGen	7.67	7.72
  NormalACRGen	4.71	4.76
  NormalBoxMullerGen	16.07	31.45
  NormalPolarGen	7.31	13.74
  NormalKindermannRamageGen	5.38	5.34

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