Hi David,
you could try a Student's t distribution with appropriate degrees of
freedom and extra scale paremter, i.e.,
?rt
rgt <- function(n, mu=0, sigma=1, df=stop("no df arg")) mu+sigma*rt(n,
df=df)
I hope this helps.
Best,
Dimitris
----
Dimitris Rizopoulos
Doctoral Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/16/396887
Fax: +32/16/337015
Web: http://www.med.kuleuven.ac.be/biostat/
http://www.student.kuleuven.ac.be/~m0390867/dimitris.htm
----- Original Message -----
From: "Crabb, David" <[EMAIL PROTECTED]>
To: <[EMAIL PROTECTED]>
Sent: Thursday, August 12, 2004 10:44 AM
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
>
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> PLEASE do read the posting guide!
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