MathGroup Archive 2004

[Date Index] [Thread Index] [Author Index]

Search the Archive

Re: Normal distribtion

  • To: mathgroup at
  • Subject: [mg49204] Re: Normal distribtion
  • From: koopman at (Ray Koopman)
  • Date: Wed, 7 Jul 2004 01:42:48 -0400 (EDT)
  • References: <> <> <ccdlms$sd5$>
  • Sender: owner-wri-mathgroup at

"Roger L. Bagula" <rlbtftn at> wrote in message news:<ccdlms$sd5$1 at>...
> I found a better faster way to get a Gaussian/ white noise:
> In Mathematica notebook style:
> x[a_]=(1+Sqrt[1-a^2))/a
> Noise=Table[Exp[-x[Sin[2*Pi*Random[]]]^2/2/Sqrt[2*Pi],{n,1,500}]
> ListPlot[noise,PlotRange--> All,PlotJoined->True]
> It is a projective line ( circle to line random taken as the basic for a 
> normal distribution's amplitude.) based algorithm.
> [...]

(1+Sqrt[1-a^2])/a = Cot[ArcSin[a]/2], so
y = x[Sin[2*Pi*Random[]]] = Cot[Pi*Random[]] has a Cauchy distribution.

Exp[-y^2/2]/Sqrt[2*Pi] is the standard normal density function, 
but why do you use it here?

  • Prev by Date: AW: factorial analysis
  • Next by Date: How to plot the surface of revolution graphics
  • Previous by thread: Re: Normal distribtion
  • Next by thread: Re: Normal distribtion