# [R] help on sampling from the truncated normal/gamma distribution on the far end (probability is very low)

Moshe Olshansky m_olshansky at yahoo.com
Fri Sep 19 03:29:40 CEST 2008

```Well, I made a mistake - your lambda should be 400 and not 40!!!

--- On Thu, 18/9/08, Moshe Olshansky <m_olshansky at yahoo.com> wrote:

> From: Moshe Olshansky <m_olshansky at yahoo.com>
> Subject: Re: [R] help on sampling from the truncated normal/gamma distribution on the far end (probability is very low)
> To: r-help at r-project.org, "Daniel Davis" <paperprint at gmail.com>
> Received: Thursday, 18 September, 2008, 5:00 PM
> Hi Sonia,
>
> If I did not make a mistake, the conditional distribution
> of X given that X > 0 is very close to exponential
> distribution with parameter lambda = 40, so you can sample
> from this distribution.
>
>
> --- On Mon, 15/9/08, Daniel Davis
> <paperprint at gmail.com> wrote:
>
> > From: Daniel Davis <paperprint at gmail.com>
> > Subject: [R] help on sampling from the truncated
> normal/gamma distribution on the far end (probability is
> very low)
> > To: r-help at r-project.org
> > Received: Monday, 15 September, 2008, 2:28 PM
> > Hi, guys,
> >
> > I am trying to sample from a truncated normal/gamma
> > distribution.
> > But only the far end of the distribution (where the
> > probability is very low)
> > is left. e.g.
> >
> > mu = - 4;
> > sigma = 0.1;
> > The distribution is Normal(mu,sigma^2) truncated on
> > [0,+Inf];
> >
> > How can I get a sample? I tried to use inverse CDF
> method,
> > but got Inf as
> >
> > Also, pls help me on the similar situation on gamma
> > dist'n.
> >
> >
> > Thanks,
> > Sonia
> >
> > 	[[alternative HTML version deleted]]
> >
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> > and provide commented, minimal, self-contained,
> > reproducible code.
>
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