R: Kriging Models using the 'libKriging' Library

# Kriging Models using the 'libKriging' Library

## Documentation for package ‘rlibkriging’ version 1.1-1

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

A B C F H I K L M N P R S T U W X Y Z

## -- A --

activation | Get activation function name
activation.MLPKriging | Get activation function for an MLPKriging model
as.km | Coerce an Object into a 'km' Object
as.km-method | Coerce a 'Kriging' object into the '"km"' class of the 'DiceKriging' package.
as.km.Kriging | Coerce a 'Kriging' object into the '"km"' class of the 'DiceKriging' package.
as.list-method | Coerce a 'Kriging' Object into a List
as.list.Kriging | Coerce a 'Kriging' Object into a List

## -- B --

beta | Get trend coefficients beta
beta.MLPKriging | Get trend coefficients beta for an MLPKriging model
beta.WarpKriging | Get trend coefficients beta for a WarpKriging model

## -- C --

centerX | Get input centering vector
centerX.MLPKriging | Get input centering vector for an MLPKriging model
centerX.WarpKriging | Get input centering vector for a WarpKriging model
centerY | Get output centering value
centerY.MLPKriging | Get output centering value for an MLPKriging model
centerY.WarpKriging | Get output centering value for a WarpKriging model
classKriging | Shortcut to provide functions to the S3 class "Kriging"
classMLPKriging | Shortcut to provide functions to the S3 class "MLPKriging"
classNestedKriging | Shortcut to provide functions to the S3 class "NestedKriging"
classWarpKriging | Shortcut to provide functions to the S3 class "WarpKriging"
copy | Duplicate object.
copy-method | Duplicate a Kriging Model
copy.Kriging | Duplicate a Kriging Model
copy.MLPKriging | Deep copy of MLPKriging model
copy.WarpKriging | Deep copy of WarpKriging model
covMat | covariance function
covMat-method | Compute Covariance Matrix of Kriging Model
covMat.Kriging | Compute Covariance Matrix of Kriging Model

## -- F --

feature_dim | Get feature dimensionality (d_out)
feature_dim.MLPKriging | Get feature dimensionality for an MLPKriging model
feature_dim.WarpKriging | Get feature dimensionality of warped space
fit | Fit model on data.
fit.Kriging | Fit 'Kriging' object on given data.
fit.MLPKriging | Fit an MLPKriging model to data
fit.WarpKriging | Fit a WarpKriging model to data
F_ | Get trend matrix F
F_.MLPKriging | Get trend matrix F for an MLPKriging model
F_.WarpKriging | Get trend matrix F for a WarpKriging model

## -- H --

hidden_dims | Get hidden layer sizes
hidden_dims.MLPKriging | Get hidden layer sizes for an MLPKriging model

## -- I --

is_fitted | Check if the model has been fitted
is_fitted.MLPKriging | Check whether an MLPKriging model is fitted
is_fitted.WarpKriging | Check whether a WarpKriging model is fitted

## -- K --

kernel | Get kernel name
kernel.WarpKriging | Get kernel name
KM | Create an 'KM' Object
KM-class | S4 class for Kriging Models Extending the '"km"' Class
Kriging | Create an object with S3 class '"Kriging"' using the 'libKriging' library.

## -- L --

leaveOneOut | Compute Leave-One-Out
leaveOneOut-method | Get leaveOneOut of Kriging Model
leaveOneOut.Kriging | Get leaveOneOut of Kriging Model
leaveOneOutFun | Leave-One-Out function
leaveOneOutFun-method | Compute Leave-One-Out (LOO) error for an object with S3 class '"Kriging"' representing a kriging model.
leaveOneOutFun.Kriging | Compute Leave-One-Out (LOO) error for an object with S3 class '"Kriging"' representing a kriging model.
leaveOneOutVec | Leave-One-Out vector
leaveOneOutVec-method | Compute Leave-One-Out (LOO) vector error for an object with S3 class '"Kriging"' representing a kriging model.
leaveOneOutVec.Kriging | Compute Leave-One-Out (LOO) vector error for an object with S3 class '"Kriging"' representing a kriging model.
load | Load any Kriging Model from a file storage. Back to base::load if not a Kriging object.
load.Kriging | Load a Kriging Model from a file storage
load.MLPKriging | Load an MLPKriging model from file
load.WarpKriging | Load a WarpKriging model from file
logLikelihood | Compute Log-Likelihood
logLikelihood-method | Get Log-Likelihood of Kriging Model
logLikelihood.Kriging | Get Log-Likelihood of Kriging Model
logLikelihood.WarpKriging | Log-likelihood of the fitted model
logLikelihoodFun | Log-Likelihood function
logLikelihoodFun-method | Compute Log-Likelihood of Kriging Model
logLikelihoodFun.Kriging | Compute Log-Likelihood of Kriging Model
logLikelihoodFun.MLPKriging | Evaluate log-likelihood at given GP theta
logLikelihoodFun.WarpKriging | Evaluate log-likelihood at given theta
logMargPost | Compute log-Marginal Posterior
logMargPost-method | Get logMargPost of Kriging Model
logMargPost.Kriging | Get logMargPost of Kriging Model
logMargPostFun | log-Marginal Posterior function
logMargPostFun-method | Compute the log-marginal posterior of a kriging model, using the prior XXXY.
logMargPostFun.Kriging | Compute the log-marginal posterior of a kriging model, using the prior XXXY.

## -- M --

M | Get whitened trend matrix M
M.MLPKriging | Get whitened trend matrix M for an MLPKriging model
M.WarpKriging | Get whitened trend matrix M for a WarpKriging model
MLPKriging | Create an MLPKriging model (Deep Kernel Learning)

## -- N --

NestedKriging | Create an object with S3 class '"NestedKriging"' using the 'libKriging' library.
NoiseKM | Create a KM object with heteroscedastic noise (deprecated)
normalize | Get normalize flag
normalize.MLPKriging | Get normalize flag for an MLPKriging model
normalize.WarpKriging | Get normalize flag for a WarpKriging model
NuggetKM | Create a KM object with nugget effect (deprecated)

## -- P --

predict-method | Prediction Method for a 'KM' Object
predict.Kriging | Predict from a 'Kriging' object.
predict.MLPKriging | Predict with an MLPKriging model
predict.NestedKriging | Predict from a 'NestedKriging' object.
predict.WarpKriging | Predict with a WarpKriging model
print.Kriging | Print the content of a 'Kriging' object.
print.NestedKriging | Print a 'NestedKriging' object.

## -- R --

regmodel | Get regression model type
regmodel.MLPKriging | Get regression model type for an MLPKriging model
regmodel.WarpKriging | Get regression model type for a WarpKriging model

## -- S --

save | Save a Kriging Model inside a file. Back to base::save if argument is not a Kriging object.
save-method | Save a Kriging Model to a file storage
save.Kriging | Save a Kriging Model to a file storage
save.MLPKriging | Save an MLPKriging model to file
save.WarpKriging | Save a WarpKriging model to file
scaleX | Get input scaling vector
scaleX.MLPKriging | Get input scaling vector for an MLPKriging model
scaleX.WarpKriging | Get input scaling vector for a WarpKriging model
scaleY | Get output scaling value
scaleY.MLPKriging | Get output scaling value for an MLPKriging model
scaleY.WarpKriging | Get output scaling value for a WarpKriging model
sigma2 | Get process variance
sigma2.WarpKriging | Get process variance (concentrated MLE)
simulate-method | Simulation from a 'KM' Object
simulate.Kriging | Simulation from a 'Kriging' model object.
simulate.MLPKriging | Simulate from an MLPKriging model
simulate.WarpKriging | Simulate from a WarpKriging model

## -- T --

theta | Get GP range parameters
theta.WarpKriging | Get GP range parameters
T_ | Get Cholesky factor T
T_.MLPKriging | Get Cholesky factor T for an MLPKriging model
T_.WarpKriging | Get Cholesky factor T for a WarpKriging model

## -- U --

update-method | Update a 'KM' Object with New Points
update.Kriging | Update a 'Kriging' model object with new points
update.MLPKriging | Update an MLPKriging model with new observations
update.WarpKriging | Update a WarpKriging model with new observations
update_simulate | Update simulation of model on data.
update_simulate.Kriging | Update previous simulation of a 'Kriging' model object.
update_simulate.MLPKriging | Update simulated paths with new observations (FOXY algorithm)
update_simulate.WarpKriging | Update simulated paths with new observations (FOXY algorithm)

## -- W --

warping | Get warping specifications as strings
warping.WarpKriging | Get warping specification for a WarpKriging model
WarpKriging | Create a WarpKriging model
warp_affine | Affine warping: w(x) = a*x + b
warp_boxcox | Box-Cox warping
warp_categorical | Categorical embedding
warp_knots | Piecewise-linear monotone warping with knots (Xiong et al. 2007)
warp_kumaraswamy | Kumaraswamy CDF warping on [0,1]
warp_mlp | Per-variable MLP warping (unconstrained, multi-dim output)
warp_neural_mono | Monotone neural network warping
warp_none | No warping (identity)
warp_ordinal | Ordinal warping (learned ordered positions)

## -- X --

X | Get training input matrix
X.MLPKriging | Get training input matrix

## -- Y --

y | Get training output vector
y.MLPKriging | Get training output vector

## -- Z --

z | Get whitened residuals z
z.MLPKriging | Get whitened residuals z for an MLPKriging model
z.WarpKriging | Get whitened residuals z for a WarpKriging model