Exactly! Thanks, Duncan.

Let me re-phrase me question like this:

1) X_i values are independent Gammas, with the shape 0.067 and scale 0.008
2) Min(X)=1 and Max(X)=85
3) SUM(X)=2000
4) Do I also have to define the number of draws? if yes, it could be 250.

Based on these restrictions, I want to generate random draw. I'm wondering
how I can do this in R. Thanks.

Garry



On Tue, Nov 10, 2009 at 11:17 AM, Duncan Murdoch <murdoch@stats.uwo.ca>wrote:

> On 11/10/2009 1:25 PM, Hongwei Dong wrote:
>
>> Hi, Dear R users,
>>
>> I'm wondering if I can do Monte Carlo Simulation in R. My problem is like
>> this: I know variable X follows Gamma distribution with shape parameter
>> 0.067 and scale parameter 0.008. The sum of the X is 2000. I need R help
>> me
>> to simulate a vector of X that satisfies both the probability distribution
>> and the sum. Anyone has a clue to this? Much appreciated.
>>
>
> Your requirements are slightly contradictory or incomplete.  Here's one way
> to fully specify the problem:
>
> The X_i values are independent Gammas, with the given shape and scale. You
> want to simulate from the joint distribution conditional on the event sum(X)
> == 2000.
>
> Is that your problem?  I don't know how to do the simulation, but maybe
> someone else does.
>
> Duncan Murdoch
>

	[[alternative HTML version deleted]]


