Man pages for ebenmichael/gaussianProcess
Fits Gaussian Processes for Regression
| gaussianProcess | Create a gaussianProcess object with a given mean function... |
| gp_lml_deriv | Compute the derivative of the log marginal likelihood |
| gp_lml_deriv_helper | Compute the derivative of the log marginal likelihood (helper... |
| gp_log_marg_like | Compute the marginal log likelihood for a GP with given data,... |
| gp_log_marg_like_helper | Compute the log marginal likelihood from parameters of the GP |
| log_marginal_like.gaussianProcess | Compute the log marginal likelihood for a GP |
| loocv.gaussianProcess | Compute the leave one out CV estimate (Rasmussen & WIllaims... |
| matern | Compute the Matern kernel between two matrices |
| optimize_hyper_params | Optimize the hyper parameters of a GP |
| pdiff | Compute the pairwise differences between X and Y |
| pdist_scaled | Compute the scaled pairwise distances between X and Y |
| plot.gaussianProcess | Plot the predictive distribution of new data. Only works with... |
| predict.gaussianProcess | Get the posterior distribution for f(X) |
| rbf | Compute the RBF (Squared Exponential) kernel between two... |
| rbf_deriv | Compute the jth partial derivative of the rbf kernel |
| sample.gaussianProcess | Sample from the posterior distribution for f(X) (or the... |
