Avoiding large matrices when computing predictive variance

[jtimonen]

Currently P x P matrices are computed for the Gaussian posterior and predictive distributions, where P is the number of prediction points. This should be avoided if only their diagonal is needed. This will require writing a function that computes only the diagonal of each kernel matrix.

[jtimonen]

Since version 1.1 computations should now require less memory because kernel matrices are only stored for one parameter set at a time.

[jtimonen]

Resolved with commit b9973051754b6f929c79a9f3d945c7824162dc30. Feature will be available in v1.1.4.