spotPredictDace: Meta Model Interface: DACE Kriging

Description Usage Arguments Value Author(s) References See Also


This Kriging meta model is based on DACE (Design and Analysis of Computer Experiments). It allows to choose different regression and correlation models. If multiple response variables are present, a DACE model for each will be created for the purpose of multi objective optimization.


spotPredictDace(rawB, mergedB, design, spotConfig, fit = NULL)



unmerged data


merged data (aggregation of repeated design points)


new design points which should be predicted


global list of all options, needed to provide data for calling functions. This also contains a list, with settings for Forrester:
spotConfig$seq.dace.budget Budget for MLE of parameters, default is 100. The value will be multiplied with the length of the model parameter vector to be optimized. (which means 100*i evaluations, where i depends on the problem dimension as well as the correlation function and whether a nugget value is to be determined)
spotConfig$seq.dace.tol Tolerance stopping criterion for MLE, default is 1e-6
spotConfig$seq.dace.regr Regression function to be used: regpoly0 (default), regpoly1, regpoly2
spotConfig$seq.dace.corr Correlation function to be used: corrnoisykriging (default), corrkriging, corrnoisygauss, corrgauss, correxp, correxpg, corrlin, corrcubic,corrspherical,corrspline
spotConfig$seq.dace.nugget Value for nugget. Default is -1, which means the nugget will be optimized during MLE. Else it can be fixed in a range between 0 and 1.


if an existing model fit is supplied, the model will not be build based on data, but only evaluated with the model fit (on the design data). To build the model, this parameter has to be NULL. If it is not NULL the parameters mergedB and rawB will not be used at all in the function.


returns the list spotConfig with two new entries:
spotConfig$seq.modelFit fit of the model used with dacePredictor
spotConfig$seq.largeDesignY the y values of the design, evaluated with the fit


The authors of the original DACE Matlab toolbox are Hans Bruun Nielsen, Soren Nymand Lophaven and Jacob Sondergaard.
Extension of the Matlab code by Tobias Wagner
Porting and adaptation to R and further extensions by Martin Zaefferer


S.~Lophaven, H.~Nielsen, and J.~Sondergaard. DACE—A Matlab Kriging Toolbox. Technical Report IMM-REP-2002-12, Informatics and Mathematical Modelling, Technical University of Denmark, Copenhagen, Denmark, 2002.

See Also

dacePredictor daceBuilder

Search within the SPOT package
Search all R packages, documentation and source code

Questions? Problems? Suggestions? or email at

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.