Scalable Gaussian Process Regression with Hierarchical Shrinkage
Priors
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Documentation for package ‘shrinkGPR’ version 1.1
Help Pages
| calc_pred_moments | Calculate Predictive Moments |
| eval_pred_dens | Evaluate Predictive Densities |
| gen_marginal_samples | Generate Marginal Samples of Predictive Distribution |
| gen_posterior_samples | Generate Posterior Samples |
| kernel_functions | Kernel Functions for Gaussian Processes |
| kernel_matern_12 | Kernel Functions for Gaussian Processes |
| kernel_matern_32 | Kernel Functions for Gaussian Processes |
| kernel_matern_52 | Kernel Functions for Gaussian Processes |
| kernel_se | Kernel Functions for Gaussian Processes |
| LPDS | Log Predictive Density Score |
| plot.shrinkGPR | Graphical summary of posterior of theta |
| plot.shrinkGPR_marg_samples_1D | Plot method for 1D marginal predictions |
| plot.shrinkGPR_marg_samples_2D | Plot method for 2D marginal predictions from 'shrinkGPR' |
| plot.shrinkTPR | Graphical summary of posterior of theta |
| predict.shrinkGPR | Generate Predictions |
| predict.shrinkTPR | Generate Predictions |
| shrinkGPR | Gaussian Process Regression with Shrinkage and Normalizing Flows |
| shrinkTPR | Student-t Process Regression with Shrinkage and Normalizing Flows |
| simGPR | Simulate Data for Gaussian Process Regression |
| sylvester | Sylvester Normalizing Flow |