Predictive mean, variance and log marginal likelihood of a GP. See "2.3 Varying the Hyperparameters" on page 19 of Rasmussen and Williams' book.
| 1 | gp.predict(y, K = NULL, Kstar, Kstarstar, U = chol(K))
 | 
| y | The targets. | 
| K | The covariance matrix (kernel) for input points, not needed if U is provided. | 
| Kstar | The cross covariance matrix (kernel) | 
| Kstarstar | The cross covariance matrix (kernel) for test points | 
| U | Cholesky decomposition of K | 
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