On Sat, Nov 6, 2010 at 8:22 PM, michael wrote:
> Jay,
>
> Yes I'm looking for unif(0,1) and your method works just fine. I
> suppose your method should work for dimensions greater than 2, am I right?
>
> Michael
>
Yes, but it gets that much more tricky to specify the covariance
matrix. Two
Jay,
Yes I'm looking for unif(0,1) and your method works just fine. I
suppose your method should work for dimensions greater than 2, am I right?
Michael
On Sat, Nov 6, 2010 at 8:05 PM, G. Jay Kerns wrote:
> Dear Michael,
>
> On Sat, Nov 6, 2010 at 7:27 PM, michael wrote:
> > Ted,
> >
>
Dear Michael,
On Sat, Nov 6, 2010 at 7:27 PM, michael wrote:
> Ted,
>
> Thanks for your help, it is right on the money!
>
> for your comments:
> 1. Yes I mean 100 by 2, each variable x1, x2 is 100 by 1.
> 2. The correlation is the only free parameter.
>
> Michael
>
>
I like Ted's solution.
Ted,
Thanks for your help, it is right on the money!
for your comments:
1. Yes I mean 100 by 2, each variable x1, x2 is 100 by 1.
2. The correlation is the only free parameter.
Michael
On Sat, Nov 6, 2010 at 7:07 PM, Ted Harding wrote:
> On 06-Nov-10 21:54:41, michael wrote:
> > I wish
On 06-Nov-10 21:54:41, michael wrote:
> I wish to generate 100 by 1 vector of x1 and x2 both are uniform
> distributed with covariance matrix \Sigma.
>
> Thanks,
> Michael
First, some comments.
1. I don't think you mean a "100 by 1 vector of x1 and x2" since
you have two variables. "100 by 2"
I wish to generate 100 by 1 vector of x1 and x2 both are uniform distributed
with covariance matrix \Sigma.
Thanks,
Michael
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