Consider using the HyperbolicDist package. With the package you can both fit the hyperbolic distribution to your data and generate random numbers from the distribution. Hyperbolic distribution/s provide/s good fit to financial returns that commonly exhibit high peaks and heavy tails.
Hannu Kahra -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of Crabb, David Sent: Thursday, August 12, 2004 10:44 AM To: [EMAIL PROTECTED] Subject: [R] Help with generating data from a 'not quite' Normal distriburtion I would be very grateful for any help from members of this list for what might be a simple problem... We are trying to simulate the behaviour of a clinical measurement in a series of computer experiments. This is simple enough to do in R if we assume the measurements to be Gaussian, but their empirical distribution has a much higher peak at the mean and the distribution has much longer tails. (The distribution is quite symmetrical) Can anyone suggest any distributions I could fit to this data, and better still how I can then generate random data from this 'distribution' using R? ----------------------------------------------- Dr. David Crabb School of Science, The Nottingham Trent University, Clifton Campus, Nottingham. NG11 8NS Tel: 0115 848 3275 Fax: 0115 848 6690 ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
