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
On Apr 28, 2011, at 12:09 PM, Ravi Varadhan wrote:
> 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?
>
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