hopsy.Gaussian.log_gradient#
- Gaussian.log_gradient(self, x)#
Computes the gradient of the logarithm of the probability density function of a multivariate Gaussian model in \(n-k\) dimensions at
x. Note that x still has to have dimension \(n\).- Parameters:
x (numpy.ndarray[n, 1]) – Input vector
- Returns:
The gradient of the (unnormalized) log_density
- Return type:
numpy.ndarray[n, 1]