EImod                   Expected improvement criterion replacement
                        function
calcTrA                 Calculates the trace of the hat matrix
calcTrAFast             Calculates the trace of the hat matrix as C
                        version
calcWdiag               Calculation of weight matrix
cancorRed               Calculate first canonical correlation
crossprodRcpp           Calculates the cross product of a matrix
devStandard             Predictive deviance of a linear model
fineTuneCvKDSN          Fine tuning of random weights of a given KDSN
                        model
fitEnsembleKDSN         Fit an ensemble of KDSN (experimental)
fitKDSN                 Fit kernel deep stacking network with random
                        Fourier transformations
fourierTransPredict     Prediction based on random Fourier
                        transformation
gDerivMu                Derivative of the link function evaluated at
                        the expected values
getEigenValuesRcpp      Calculates the eigenvalues of a matrix
kernDeepStackNet-package
                        Kernel deep stacking networks with random
                        Fourier transformation
kernDeepStackNet_crossprodRcpp
                        Calculates the cross product of a matrix
kernDeepStackNet_getEigenValuesRcpp
                        Calculates the eigenvalues of a matrix
lossApprox              Kernel deep stacking network loss function
lossCvKDSN              Kernel deep stacking network loss function
                        based on cross-validation
lossGCV                 Generalized cross-validation loss
lossSharedCvKDSN        Kernel deep stacking network loss function
                        based on cross-validation and shared
                        hyperparameters
lossSharedTestKDSN      Kernel deep stacking network loss function with
                        test set and shared hyperparameters
mbo1d                   Efficient global optimization with iterative
                        point proposals
mboAll                  Efficient global optimization inclusive meta
                        model validation
optimize1dMulti         One dimensional optimization of multivariate
                        loss functions
predLogProb             Predictive logarithmic probability of Kriging
                        model
predict.KDSN            Predict kernel deep stacking networks
predict.KDSNensemble    Predict kernel deep stacking networks ensembles
                        (experimental)
predict.KDSNensembleDisk
                        Predict kernel deep stacking networks ensembles
                        (experimental)
randomFourierTrans      Random Fourier transformation
rdcPart                 Randomized dependence coefficient partial
                        calculation
rdcSubset               Randomized dependence coefficients score on
                        given subset
rdcVarOrder             Variable ordering using randomized dependence
                        coefficients (experimental)
rdcVarSelSubset         Variable selection based on RDC with genetic
                        algorithm (experimental)
robustStandard          Robust standardization
tuneMboLevelCvKDSN      Tuning of KDSN with efficient global
                        optimization given level by cross-validation
tuneMboLevelGcvKDSN     Tuning of KDSN with efficient global
                        optimization given level by cross-validation
tuneMboSharedCvKDSN     Tuning of KDSN with efficient global
                        optimization given level by cross-validation
                        and shared hyperparameters
tuneMboSharedSubsetKDSN
                        Tuning subsets of KDSN with efficient global
                        optimization and shared hyperparameters
                        (experimental)
varMu                   Variance function evaluated at expected value
