DiceKriging v1.5.5
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Kriging Methods for Computer Experiments
Estimation, validation and prediction of kriging models.
Important functions : km, print.km, plot.km, predict.km.
Functions in DiceKriging
| Name | Description | |
| SCAD | Penalty function | |
| show | Print values of a km object | |
| kernelname | Get the kernel name | |
| covVector.dx | Spatial covariance - Derivatives | |
| covKernel-class | Class "covKernel" | |
| km-class | Kriging models class | |
| covScaling-class | Class "covScaling" | |
| DiceKriging-package | Kriging Methods for Computer Experiments | |
| SCAD.derivative | Penalty function derivative | |
| plot | Diagnostic plot for the validation of a km object | |
| covTensorProduct-class | Class of tensor-product spatial covariances | |
| covAffineScaling-class | Class "covAffineScaling" | |
| covUser-class | Class "covUser" | |
| nuggetflag | Get the nugget flag | |
| hartman3 | 3D test function | |
| leaveOneOutGrad | Leave-one-out least square criterion - Analytical gradient | |
| branin | 2D test function | |
| trend.deltax | Trend derivatives | |
| computeAuxVariables | Auxiliary variables for kriging | |
| drop.response | Trend model formula operation | |
| camelback | 2D test function | |
| scalingFun | Scaling function | |
| scalingGrad | Gradient of the dimensional Scaling function | |
| leaveOneOutFun | Leave-one-out least square criterion of a km object | |
| covParametersBounds | Boundaries for covariance parameters | |
| kmNoNugget.init | Fitting Kriging Models | |
| goldsteinPrice | 2D test function | |
| km | Fit and/or create kriging models | |
| trendMatrix.update | Trend model matrix operation | |
| predict | Predict values and confidence intervals at newdata for a km object | |
| checkNames | Consistency test between the column names of two matrices | |
| kmNuggets.init | Fitting Kriging Models | |
| covMat1Mat2 | Cross covariance matrix | |
| km1Nugget.init | Fitting Kriging Models | |
| affineScalingGrad | Gradient of the Scaling function (affine case) | |
| covStruct.create | Spatial covariance - Class constructor | |
| nuggetvalue | Get or set the nugget value | |
| hartman6 | 6D test function | |
| ninput | Get the spatial dimension | |
| inputnames | Get the input variables names | |
| covMatrixDerivative | Covariance matrix derivatives | |
| logLik | log-likelihood of a km object | |
| kmData | Fit and/or create kriging models | |
| affineScalingFun | Scaling function (affine case) | |
| leaveOneOut.km | Leave-one-out for a km object | |
| simulate | Simulate GP values at any given set of points for a km object | |
| covMatrix | Covariance matrix | |
| kmEstimate | Fitting Kriging Models | |
| covparam2vect | Auxiliary function | |
| covIso-class | Class of tensor-product spatial covariances with isotropic range | |
| coef | Get coefficients values | |
| logLikGrad | Concentrated log-Likelihood of a km object - Analytical gradient | |
| logLikFun | Concentrated log-likelihood of a km object | |
| update | Update of a kriging model | |
| vect2covparam | Auxiliary function | |
| No Results! | ||
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Details
| Date | 2015-04-23 |
| License | GPL-2 | GPL-3 |
| URL | http://dice.emse.fr/ |
| Packaged | 2015-04-24 06:25:18 UTC; roustant |
| NeedsCompilation | yes |
| Repository | CRAN |
| Date/Publication | 2015-04-24 11:22:56 |
| suggests | doParallel , foreach , rgenoud , testthat |
| depends | methods |
| Contributors | Olivier Roustant, David Ginsbourger, Yves Contributors: Clement Chevalier, Yann Richet |
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