Re: Cumulative distribution of Gauss
- To: mathgroup at smc.vnet.net
- Subject: [mg18744] Re: Cumulative distribution of Gauss
- From: Denis Cousineau <decousin at indiana.edu>
- Date: Sat, 17 Jul 1999 02:36:54 -0400
- Organization: Indiana University
- References: <7mjqqb$f2v@smc.vnet.net>
- Sender: owner-wri-mathgroup at wolfram.com
Hi, using mathematica, obtaining values of distributions (gaussian=normal, or any other) is pretty easy. the cumulative density function (CDF) of the normal distribution is define if you importe the continuous distribution package using << Statistics`ContinuousDistributions` Then, you ask the values you need with CDF[NormalDistribution[mu,sigma],x] where mu and sigma are the mean and standard deviation of the gaussian you have in mind (or 0 and 1 for the standard gaussian). ================================================================= If you are not using Mathematica, then, you may use the function erf, defined in most not-too-hold programing languages (and in most c language on unix station). The erf function approximate the correct integral using fast and very accurate algorithms. The error function erf(x) is used to approximate the normal=gaussian standard cumulative function in the following formula: 1/2 (1 + erf[(x-mu)/(Sqrt(2) sigma)] ) J'espere que ca vous aide. N'hesitez pas si vous avez besoin de plus d'information. Denis. sallier_daniel at wanadoo.fr wrote: > > Is there any analytical expression of the cumulative distribution of Gauss ? > If not, can someone provided me with a fast executing algorithm. I am > currently using pre-tabulated data. It is fine but its ends up to be rather > time consuming for highly iterative calculations. > > Thank you for assistance. > > D. SALLIER > > sallier_daniel at wanadoo.fr -- Denis Cousineau, Postdoc ***************************** Cognitive psychology * * Indiana University * Etudiant devant l'eternel * Psychology Building * * Bloomington, 47405 ***************************** Office: (812) 856-5217 Fax: (812) 855-1086 E-mail: decousin at indiana.edu http://Prelude.PSY.UMontreal.CA/~cousined