[R] transform normally distributed random terms to gamma distributed random terms

[Spencer Graves]

	  1.  The help page for ?rgamma says E(g) = shape*scale = shape/rate 
and var(g) = shape*scale^2 = shape/rate^2.  These are different from 
what I read in your email.  Could you please check the help page more 
carefully?

	  2.  If this does not solve your problem, PLEASE do read the posting 
guide! "http://www.R-project.org/posting-guide.html".  Many people 
answer their own questions in the process of preparing a posting.  If 
they don't find the answer, their question is more likely to elicit 
useful replies.  In particular, please include a brief example 
explaining why you think "rgamma" won't work for you, nor why something 
like qgamma(runif(...)) nor qgamma(pnorm(rnorm(...)))?

	  hope this helps.
	  spencer graves

Stefan Pohl wrote:
> Hi,
> 
> I have normally distributed random terms u~N(0,1). I want to get gamma distributed random terms g~(scale,shape) with
> E(g)=1=shape/scale and var(g)=theta=1/scale=1/shape. 
> 
> How can I reach my goal? The following way doesn't work: use the distribution function of u to get U(0,1)- distributed random
> terms, then take the quantile function of the gamma distribution with shape and scale.
> 
> The resulting random terms must be ~gamma(shape, scale).
> 
> But it doesn't work.
> 
> Is there a mistake or do you know another way?
> 
> Thanks, Stefan.
> 	[[alternative HTML version deleted]]
> 
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