Kriging Models using the 'libKriging' Library
Compute Covariance Matrix of NoiseKriging Model
Compute Covariance Matrix of NuggetKriging Model
covariance function
Load any Kriging Model from a file storage. Back to base::load if not ...
Get Log-Likelihood of Kriging Model
Get logLikelihood of NoiseKriging Model
Get logLikelihood of NuggetKriging Model
Compute Log-Likelihood
Compute Log-Likelihood of Kriging Model
Compute the log-marginal posterior of a kriging model, using the prior...
log-Marginal Posterior function
Duplicate a NoiseKriging Model
Duplicate a NuggetKriging Model
Duplicate object.
Compute Covariance Matrix of Kriging Model
Load a Kriging Model from a file storage
Load a NoiseKriging Model from a file storage
Load a NuggetKriging Model from a file storage
Save a Kriging Model inside a file. Back to base::save if argument is ...
Coerce a NuggetKriging Object into a List
Shortcut to provide functions to the S3 class "Kriging"
Shortcut to provide functions to the S3 class "NoiseKriging"
Shortcut to provide functions to the S3 class "NuggetKriging"
Duplicate a Kriging Model
Coerce a NoiseKriging Object into a List
Coerce a Kriging object into the "km" class of the DiceKriging p...
Coerce a NoiseKriging object into the "km" class of the `DiceKrigi...
Coerce a NuggetKriging object into the "km" class of the `DiceKrig...
Coerce an Object into a km Object
Coerce a Kriging Object into a List
Fit Kriging object on given data.
Fit NoiseKriging object on given data.
Fit NuggetKriging object on given data.
Fit model on data.
S4 class for Kriging Models Extending the "km" Class
Create an KM Object
Create an object with S3 class "Kriging" using the libKriging libr...
Get leaveOneOut of Kriging Model
Compute Leave-One-Out
Compute Leave-One-Out (LOO) error for an object with S3 class `"Krigin...
Leave-One-Out function
Compute Leave-One-Out (LOO) vector error for an object with S3 class `...
Leave-One-Out vector
Compute Log-Likelihood of NoiseKriging Model
Compute Log-Likelihood of NuggetKriging Model
Log-Likelihood function
Get logMargPost of Kriging Model
Get logMargPost of NuggetKriging Model
Compute log-Marginal Posterior
Compute the log-marginal posterior of a kriging model, using the prior...
S4 class for NoiseKriging Models Extending the "km" Class
Create an NoiseKM Object
Create an object with S3 class "NoiseKriging" using the libKriging...
S4 class for NuggetKriging Models Extending the "km" Class
Create an NuggetKM Object
Create an object with S3 class "NuggetKriging" using the `libKriging...
Prediction Method for a KM Object
Prediction Method for a NoiseKM Object
Prediction Method for a NuggetKM Object
Predict from a Kriging object.
Predict from a NoiseKriging object.
Predict from a NuggetKriging object.
Print the content of a Kriging object.
Print the content of a NoiseKriging object.
Print the content of a NuggetKriging object.
Save a Kriging Model to a file storage
Save a NoiseKriging Model to a file storage
Save a NuggetKriging Model to a file storage
Simulation from a KM Object
Simulation from a NoiseKM Object
Simulation from a NuggetKM Object
Simulation from a Kriging model object.
Simulation from a NoiseKriging model object.
Simulation from a NuggetKriging model object.
Update previous simulation of a Kriging model object.
Update previous simulation of a NoiseKriging model object.
Update previous simulation of a NuggetKriging model object.
Update simulation of model on data.
Update a KM Object with New Points
Update a NoiseKM Object with New Points
Update a NuggetKM Object with New Points
Update a Kriging model object with new points
Update a NoiseKriging model object with new points
Update a NuggetKriging model object with new points
Interface to 'libKriging' 'C++' library <https://github.com/libKriging> that should provide most standard Kriging / Gaussian process regression features (like in 'DiceKriging', 'kergp' or 'RobustGaSP' packages). 'libKriging' relies on Armadillo linear algebra library (Apache 2 license) by Conrad Sanderson, 'lbfgsb_cpp' is a 'C++' port around by Pascal Have of 'lbfgsb' library (BSD-3 license) by Ciyou Zhu, Richard Byrd, Jorge Nocedal and Jose Luis Morales used for hyperparameters optimization.