how to generate a normal distribution with mean=1, min=0.2, max=0.8

That method (creating lots of samples and throwing most of them away) is 
usually frowned upon :-).

Try this:  (I haven't, so it may well have syntax errors)

% n28<- dnorm(seq(.2,.8,by=.001),mean=1,sd=1)

% x <- sample(seq(.2,.8,by=.001), size=500,replace=TRUE, prob=n28)

And I guess in retrospect this  will get really ugly if you want, say, a 
sampling grid resolution of 1e-6 or so.

Anyone know what's applicable from the "sampling" package?


Carl

-------<quote>__________________
From: David Winsemius <dwinsemius_at_comcast.net>
Date: Thu, 28 Apr 2011 13:06:21 -0400

> Surely you must be joking, Mr. Jianfeng.
 >

Perhaps not joking and perhaps not with correct statistical specification.

A truncated Normal could be simulated with:

set.seed(567)
x <- rnorm(n=50000, m=1, sd=1)
xtrunc <- x[x>=0.2 & x <=0.8]
require(logspline)
plot(logspline(xtrunc, lbound=0.2, ubound=0.8, nknots=7))

David.




 > -----Original Message-----

 > From: r-help-bounces_at_r-project.org 
[mailto:r-help-bounces_at_r-project.org

 > ] On Behalf Of Mao Jianfeng



 > Dear all,

 >

 > This is a simple probability problem. I want to know, How to

 > generate a

 > normal distribution with mean=1, min=0.2 and max=0.8?

 >