[SciPy-user] Generating random variables in a joint normal distribution?

[Parvel Gu]

Hi,

Thanks so much for the reply. I could go furthur in this problem.

And here is the following issue:

In my understanding, the continues calls to random.multivariate_normal
would get a serials of random vairables which are all following the
joint normal distribution. Then what about how to reset the random
generating in each iteration?

Assuming that I have to simulate something for 50 iterations then to
get the average value. In each iteration I need a serial of random
pairs which follows the joint normal distrubition. The interations are
expected to be independent to each other.

Thus:

In iteration 1:
       serial = []
       in sub loop
          serial.append(random.multivariate_normal(m, cov))
       ...

And in iteration 2, I want a fresh serial which should not be affected
by the previous one        s. Is there any problem to empty the serial
then still call  random.multivariate_normal(m, cov) ?
In my understanding if there is no refresh or something performed to
the internal random generator, the random.multivariate_normal would
continue to generate variables in the context of the previous ones.

Br,
Parvel