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Update Gaussian Process Models in Stan Reference Manual #16
There are some of GP models in the Example Models/Gaussian Process Section of the Reference Manual that are invalid, and there also need be updated for some of the new kernels.
I will make a list of things I've noticed, and this is in no way designed to be comprehensive, and I will update this post as I go:
This does not make sense. We simply need two x vectors:
then we generate predictions for indeces greater than
Instead, we use matrix algebra (i.e. using the posterior predictive mean function and posterior predictive variance, and then the
assuming we generate the predictive posterior correctly, and there is an example below.
This wasn't as organized as I'd hoped but it hits on some points.
If you copy and paste some of the notation in the Stan manual and plot the in sample predictive distribution, you will see what I'm talking about.
@drezap great point on points 2 and 3 for the prediction function, we should add this code to the manual. Just a note, the code in the user guide for the predictions using the latent functions isn't wrong, it's just not as efficient as it could be, as you rightly point out. Re the form for Gaussian models see pages 152 to 154 in the new guide. I wrote the section in the user guide to be more pedagogical, but I can see an argument for not including any inefficient code in the manual, even if it's used as a building block for later more efficient code.