Optimization

optimize!(gp::GPBase; kwargs...)

Optimise the hyperparameters of Gaussian process gp based on type II maximum likelihood estimation. This function performs gradient based optimisation using the Optim pacakge to which the user is referred to for further details.

Keyword arguments:

* `domean::Bool`: Mean function hyperparameters should be optmized
* `kern::Bool`: Kernel function hyperparameters should be optmized
* `noise::Bool`: Observation noise hyperparameter should be optimized (GPE only)
* `lik::Bool`: Likelihood hyperparameters should be optimized (GPA only)
* `meanbounds`: [lowerbounds, upperbounds] for the mean hyperparameters
* `kernbounds`: [lowerbounds, upperbounds] for the kernel hyperparameters
* `noisebounds`: [lowerbound, upperbound] for the noise hyperparameter
* `kwargs`: Keyword arguments for the optimize function from the Optim package