Robert Kern robert.kern at gmail.com writes:
On Thu, Sep 18, 2008 at 16:55, Paul Moore pf_moore at yahoo.co.uk wrote:
I want to generate a series of random samples, to do simulations based
on them. Essentially, I want to be able to produce a SAMPLESIZE * N
matrix, where each row of N values
On Friday 19 September 2008 05:08:20 Paul Moore wrote:
Robert Kern robert.kern at gmail.com writes:
On Thu, Sep 18, 2008 at 16:55, Paul Moore pf_moore at yahoo.co.uk
wrote:
I want to generate a series of random samples, to do simulations based
on them. Essentially, I want to be able to
2008/9/19 Paul Moore [EMAIL PROTECTED]:
Robert Kern robert.kern at gmail.com writes:
On Thu, Sep 18, 2008 at 16:55, Paul Moore pf_moore at yahoo.co.uk wrote:
I want to generate a series of random samples, to do simulations based
on them. Essentially, I want to be able to produce a SAMPLESIZE
Rick White rlw at stsci.edu writes:
It seems like numpy.random.permutation is pretty suboptimal in its
speed. Here's a Python 1-liner that does the same thing (I think)
but is a lot faster:
a = 1+numpy.random.rand(M).argsort()[0:N-1]
This still has the the problem that it generates
I want to generate a series of random samples, to do simulations based
on them. Essentially, I want to be able to produce a SAMPLESIZE * N
matrix, where each row of N values consists of either
1. Integers between 1 and M (simulating M rolls of an N-sided die), or
2. A sample of N numbers
On Thu, Sep 18, 2008 at 16:55, Paul Moore [EMAIL PROTECTED] wrote:
I want to generate a series of random samples, to do simulations based
on them. Essentially, I want to be able to produce a SAMPLESIZE * N
matrix, where each row of N values consists of either
1. Integers between 1 and M
