NumPy: simultaneous sampling from multivariate Gaussians with matrix of means
I have an N by P matrix in which in which the n-th row is a P-vector representing the mean for a multivariate Gaussian and a P by P matrix Sigma representing a shared covariance matrix.
Is there any way to sample from all N multivariate Gaussians in NumPy faster than using a for loop?
Normal = np.random.multivariate_normal
for n in range(N):
X[n] = Normal(mean=mu[n], cov=Sigma)
performance numpy
asked Nov 14 '18 at 17:03
gwggwg
4,24053365
add a comment |
I have an N by P matrix in which in which the n-th row is a P-vector representing the mean for a multivariate Gaussian and a P by P matrix Sigma representing a shared covariance matrix.
Is there any way to sample from all N multivariate Gaussians in NumPy faster than using a for loop?
Normal = np.random.multivariate_normal
for n in range(N):
X[n] = Normal(mean=mu[n], cov=Sigma)
performance numpy
asked Nov 14 '18 at 17:03
gwggwg
4,24053365
This looks like a duplicate of stackoverflow.com/questions/49681124/… (but simpler, because you have just one covariance matrix).
– Warren Weckesser
Nov 14 '18 at 17:56
add a comment |
I have an N by P matrix in which in which the n-th row is a P-vector representing the mean for a multivariate Gaussian and a P by P matrix Sigma representing a shared covariance matrix.
Is there any way to sample from all N multivariate Gaussians in NumPy faster than using a for loop?
Normal = np.random.multivariate_normal
for n in range(N):
X[n] = Normal(mean=mu[n], cov=Sigma)
performance numpy
asked Nov 14 '18 at 17:03
gwggwg
4,24053365
I have an N by P matrix in which in which the n-th row is a P-vector representing the mean for a multivariate Gaussian and a P by P matrix Sigma representing a shared covariance matrix.
Is there any way to sample from all N multivariate Gaussians in NumPy faster than using a for loop?
Normal = np.random.multivariate_normal
for n in range(N):
X[n] = Normal(mean=mu[n], cov=Sigma)
performance numpy
performance numpy
asked Nov 14 '18 at 17:03
gwggwg
4,24053365
asked Nov 14 '18 at 17:03
gwggwg
4,24053365
asked Nov 14 '18 at 17:03
gwggwg
4,24053365
asked Nov 14 '18 at 17:03
gwggwg
4,24053365
asked Nov 14 '18 at 17:03
gwggwg
4,24053365
4,24053365
This looks like a duplicate of stackoverflow.com/questions/49681124/… (but simpler, because you have just one covariance matrix).
– Warren Weckesser
Nov 14 '18 at 17:56
add a comment |
This looks like a duplicate of stackoverflow.com/questions/49681124/… (but simpler, because you have just one covariance matrix).
– Warren Weckesser
Nov 14 '18 at 17:56
This looks like a duplicate of stackoverflow.com/questions/49681124/… (but simpler, because you have just one covariance matrix).
– Warren Weckesser
Nov 14 '18 at 17:56
This looks like a duplicate of stackoverflow.com/questions/49681124/… (but simpler, because you have just one covariance matrix).
– Warren Weckesser
Nov 14 '18 at 17:56
add a comment |
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This looks like a duplicate of stackoverflow.com/questions/49681124/… (but simpler, because you have just one covariance matrix).
– Warren Weckesser
Nov 14 '18 at 17:56