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This repository is just a wrapper to emulate a "standard" R package from https://github.com/libKriging/bindings/R/rlibkriging content, so you can install it just using:

install.packages('devtools')
devtools::install_github("libKriging/rlibkriging")

# Or install a specific tagged version
devtools::install_github("libKriging/[email protected]")

Note: When installing via install_github(), the package automatically initializes git submodules (src/libK, src/slapack) at the correct versions using the pinned commits recorded in tools/gitmodules-shas. This ensures you get the exact versions of dependencies that were used when the release was tagged.

The stable version is available from CRAN :

install.packages('rlibkriging')

Requirements

Note: this repository mainly contains modified Makefiles, inspired by https://github.com/astamm/nloptr wrapper.

CRAN

When submitting to CRAN, ./tools/setup.sh should be run before R CMD build rlibkriging to fit CRAN policy.

Submodule Version Management

For maintainers: when updating submodules, always run ./tools/update_submodule_shas.sh to record the new commit SHAs. This ensures users who install via install_github() get the correct submodule versions. See SUBMODULE_VERSION_MANAGEMENT.md for details.

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Version

Install

install.packages('rlibkriging')

Monthly Downloads

694

Version

1.2-3

License

Apache License (>= 2)

Maintainer

Yann Richet

Last Published

September 25th, 2026

Functions in rlibkriging (1.2-3)

as.km

Coerce an Object into a km Object
centerY.WarpKriging

Get output centering value for a WarpKriging model
copy.MLPKriging

Deep copy of MLPKriging model
activation.MLPKriging

Get activation function for an MLPKriging model
copy

Duplicate object.
beta

Get trend coefficients beta
X

Get training input matrix
beta.MLPKriging

Get trend coefficients beta for an MLPKriging model
centerY.MLPKriging

Get output centering value for an MLPKriging model
as.list.Kriging

Coerce a Kriging Object into a List
centerY

Get output centering value
kernel

Get kernel name
kernel.WarpKriging

Get kernel name
as.km.Kriging

Coerce a Kriging object into the "km" class of the DiceKriging package.
covMat.Kriging

Compute Covariance Matrix of Kriging Model
classKriging

Shortcut to provide functions to the S3 class "Kriging"
copy.WarpKriging

Deep copy of WarpKriging model
fit

Fit model on data.
fit.MLPKriging

Fit an MLPKriging model to data
fit.WarpKriging

Fit a WarpKriging model to data
feature_dim.WarpKriging

Get feature dimensionality of warped space
fit.Kriging

Fit Kriging object on given data.
hidden_dims.MLPKriging

Get hidden layer sizes for an MLPKriging model
logLikelihoodFun.WarpKriging

Evaluate log-likelihood at given theta
logMargPost.Kriging

Get logMargPost of Kriging Model
leaveOneOutVec

Leave-One-Out vector
leaveOneOutVec.Kriging

Compute Leave-One-Out (LOO) vector error for an object with S3 class "Kriging" representing a kriging model.
classMLPKriging

Shortcut to provide functions to the S3 class "MLPKriging"
classNestedKriging

Shortcut to provide functions to the S3 class "NestedKriging"
beta.WarpKriging

Get trend coefficients beta for a WarpKriging model
centerX.MLPKriging

Get input centering vector for an MLPKriging model
normalize.MLPKriging

Get normalize flag for an MLPKriging model
noise.WarpKriging

Get per-observation noise variances for a WarpKriging model
leaveOneOut.Kriging

Get leaveOneOut of Kriging Model
load.Kriging

Load a Kriging Model from a file storage
leaveOneOut

Compute Leave-One-Out
save.Kriging

Save a Kriging Model to a file storage
load.MLPKriging

Load an MLPKriging model from file
logMargPostFun

log-Marginal Posterior function
noise

Get per-observation noise variances
logLikelihood.Kriging

Get Log-Likelihood of Kriging Model
hidden_dims

Get hidden layer sizes
centerX

Get input centering vector
save.MLPKriging

Save an MLPKriging model to file
logLikelihood

Compute Log-Likelihood
scaleX.MLPKriging

Get input scaling vector for an MLPKriging model
logMargPost

Compute log-Marginal Posterior
normalize.WarpKriging

Get normalize flag for a WarpKriging model
simulate,KM-method

Simulation from a KM Object
logMargPostFun.Kriging

Compute the log-marginal posterior of a kriging model, using the prior XXXY.
scaleX

Get input scaling vector
normalize

Get normalize flag
covMat

covariance function
predict.WarpKriging

Predict with a WarpKriging model
regmodel

Get regression model type
regmodel.WarpKriging

Get regression model type for a WarpKriging model
simulate.WarpKriging

Simulate from a WarpKriging model
is_fitted.MLPKriging

Check whether an MLPKriging model is fitted
centerX.WarpKriging

Get input centering vector for a WarpKriging model
update_simulate.MLPKriging

Update simulated paths with new observations (FOXY algorithm)
covMat.WarpKriging

Covariance matrix between two sets of points (warped kernel)
print.Kriging

Print the content of a Kriging object.
simulate.MLPKriging

Simulate from an MLPKriging model
simulate.Kriging

Simulation from a Kriging model object.
print.NestedKriging

Print a NestedKriging object.
scaleY.MLPKriging

Get output scaling value for an MLPKriging model
theta

Get GP range parameters
regmodel.MLPKriging

Get regression model type for an MLPKriging model
subsetOfData

Subset-of-data pre-fit reduction.
scaleX.WarpKriging

Get input scaling vector for a WarpKriging model
copy.Kriging

Duplicate a Kriging Model
warp_neural_mono

Monotone neural network warping
z.MLPKriging

Get whitened residuals z for an MLPKriging model
classWarpKriging

Shortcut to provide functions to the S3 class "WarpKriging"
warp_mlp

Per-variable MLP warping (unconstrained, multi-dim output)
feature_dim

Get feature dimensionality (d_out)
feature_dim.MLPKriging

Get feature dimensionality for an MLPKriging model
update_simulate

Update simulation of model on data.
update.Kriging

Update a Kriging model object with new points
update.MLPKriging

Update an MLPKriging model with new observations
leaveOneOutFun

Leave-One-Out function
leaveOneOutFun.Kriging

Compute Leave-One-Out (LOO) error for an object with S3 class "Kriging" representing a kriging model.
update_simulate.WarpKriging

Update simulated paths with new observations (FOXY algorithm)
warp_affine

Affine warping: w(x) = a*x + b
warping.WarpKriging

Get warping specification for a WarpKriging model
warping

Get warping specifications as strings
warp_ordinal

Ordinal warping (learned ordered positions)
warp_none

No warping (identity)
is_fitted

Check if the model has been fitted
load

Load any Kriging Model from a file storage. Back to base::load if not a Kriging object.
is_fitted.WarpKriging

Check whether a WarpKriging model is fitted
warp_params

Get the packed warping parameters
warp_categorical

Categorical embedding
warp_boxcox

Box-Cox warping
warp_params.WarpKriging

Get the packed warping parameters for a WarpKriging model
logLikelihood.WarpKriging

Log-likelihood of the fitted model
logLikelihoodFun.Kriging

Compute Log-Likelihood of Kriging Model
z

Get whitened residuals z
save

Save a Kriging Model inside a file. Back to base::save if argument is not a Kriging object.
predict,KM-method

Prediction Method for a KM Object
predict.NestedKriging

Predict from a NestedKriging object.
predict.MLPKriging

Predict with an MLPKriging model
logLikelihoodFun.MLPKriging

Evaluate log-likelihood at given GP theta
logLikelihoodFun

Log-Likelihood function
save.WarpKriging

Save a WarpKriging model to file
load.WarpKriging

Load a WarpKriging model from file
sigma2

Get process variance
sigma2.WarpKriging

Get process variance (concentrated MLE)
y.MLPKriging

Get training output vector
warp_knots

Piecewise-linear monotone warping with knots (Xiong et al. 2007)
update,KM-method

Update a KM Object with New Points
warp_kumaraswamy

Kumaraswamy CDF warping on [0,1]
theta.WarpKriging

Get GP range parameters
scaleY.WarpKriging

Get output scaling value for a WarpKriging model
update.WarpKriging

Update a WarpKriging model with new observations
predict.Kriging

Predict from a Kriging object.
y

Get training output vector
scaleY

Get output scaling value
z.WarpKriging

Get whitened residuals z for a WarpKriging model
update_simulate.Kriging

Update previous simulation of a Kriging model object.
M.MLPKriging

Get whitened trend matrix M for an MLPKriging model
F_.MLPKriging

Get trend matrix F for an MLPKriging model
Kriging

Create an object with S3 class "Kriging" using the libKriging library.
KM

Create an KM Object
F_.WarpKriging

Get trend matrix F for a WarpKriging model
M

Get whitened trend matrix M
KM-class

S4 class for Kriging Models Extending the "km" Class
MLPKriging

Create an MLPKriging model (Deep Kernel Learning)
F_

Get trend matrix F
M.WarpKriging

Get whitened trend matrix M for a WarpKriging model
WarpKriging

Create a WarpKriging model
X.MLPKriging

Get training input matrix
NuggetKM

Create a KM object with nugget effect (deprecated)
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
activation

Get activation function name
NestedKriging

Create an object with S3 class "NestedKriging" using the libKriging library.
NoiseKM

Create a KM object with heteroscedastic noise (deprecated)