Compute the gradient of the negative log-likelihood of a Gaussian Process.
logLikGrad(
par = model$kernParam$par,
model,
parfixed = rep(FALSE, length(par)),
mcmc.opts = NULL,
estim.varnoise = FALSE
)the values of the covariance parameters.
an object with "lineqGP" S3 class.
indices of fixed parameters to do not be optimised.
not used.
If true, a noise variance is estimated.
the gradient of the negative log-likelihood.
Rasmussen, C. E. and Williams, C. K. I. (2005), "Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)". The MIT Press. [link]