Description Usage Arguments Value
Compute the derivative of the log marginal likelihood
1 | gp_lml_deriv(hyper.params, X, y, kernel.type, order = 5/2, noise.var = 1)
|
hyper.params |
Hyper parameters as a vector (for rbf c(amplitude, scales)) |
X |
An n x d matrix of covariates for observed data |
y |
An n dimensional vector of outputs for observed data |
kernel.type |
The kernel function to use |
order |
The order of the kernel, defaults to 5/2 |
noise.var |
The variance of the noise around the function |
The gradient of the log marginal likelihood at hyper.params
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