| cocons-package | Covariate-based Covariance Functions for Nonstationary Gaussian Processes |
| coco | Creates a coco S4 object |
| coco-class | An S4 class to store information |
| cocons | Covariate-based Covariance Functions for Nonstationary Gaussian Processes |
| cocoOptim | Optimizer for coco objects |
| cocoPredict | Prediction for coco objects |
| cocoSim | Marginal and conditional simulation of nonstationary Gaussian processes |
| cov_rns | Dense covariance function (difference parameterization) |
| cov_rns_classic | Dense covariance function (classic parameterization) |
| cov_rns_pred | Dense covariance function |
| cov_rns_taper | Sparse covariance function |
| cov_rns_taper_pred | Sparse covariance function |
| getAIC | Retrieve AIC |
| getBIC | Retrieve BIC |
| getBoundaries | Simple build of boundaries |
| getBoundariesV2 | Simple build of boundaries (v2) |
| getBoundariesV3 | Simple build of boundaries (v3) |
| getCIs | Compute approximate confidence intervals for a coco object |
| getCovMatrix | Covariance matrix for "coco" class |
| getCRPS | Based on a set of predictions computes the Continuous Ranked Probability Score |
| getDensityFromDelta | Based on a specific taper scale (delta), retrieves the density of the covariance matrix. |
| getDesignMatrix | Create an efficient design matrix based on a list of aspect models |
| getEstims | Retrieve estimates from a fitted coco object |
| getHessian | getHessian |
| getLoglik | Retrieve the loglikelihood value |
| getLogScore | Based on a set of predictions computes the Log-Score |
| getModelLists | Builds the necessary input for building covariance matrices |
| getModHess | Retrieves the modified inverse of the hessian |
| GetNeg2loglikelihood | GetNeg2loglikelihood |
| GetNeg2loglikelihoodProfile | GetNeg2loglikelihoodProfile |
| GetNeg2loglikelihoodREML | GetNeg2loglikelihoodREML |
| GetNeg2loglikelihoodTaper | GetNeg2loglikelihoodTaper |
| GetNeg2loglikelihoodTaperProfile | GetNeg2loglikelihoodTaperProfile |
| getScale | Fast and simple standardization for the design matrix. |
| getSpatEffects | Evaluates the spatially-varying functions from a coco object at locs |
| getSpatMean | Computes the spatial mean of a (fitted) coco object |
| holes | Holes Data Set |
| holes_bm | Holes with trend + multiple realizations Data Set |
| is.formula | check whether an R object is a formula |
| plot-method | Plot Method for coco objects |
| plotOptimInfo | Plot log info detailed |
| stripes | Stripes Data Set |
| summary | Summary Method for Coco Class |
| summary-method | Summary Method for Coco Class |