Python/Numpy: Conditional simulation from a multivatiate distribution
<p>Using numpy I can simulate unconditionally from a multivariate normal distribution by</p>

<pre><code>mean = [0, 0]
cov = [[1, 0], [0, 100]]  # diagonal covariance
x, y = np.random.multivariate_normal(mean, cov, 5000).T
</code></pre>

<p>How do I simulate y from the same distribution, given that I have 5000 realizations of x? I'm looking for a generalized solution that can be scaled to an arbitrary dimension.</p>