DACE - A Matlab Kriging Toolbox, Version 2.0

By S. Lophaven, H. B. Nielsen, Jacob Søndergaard. 2002

614 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/d51bcfd7152816293ee937f40d7d6b259ec7511d

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Citations in the corpus

Predictive quantification of surrogate model fidelity based on modal variations with sample density (2015, methodology): “To implement the Kriging method, the DACE (design and analysis of computer experiments) package developed by Lophaven et al. (2002) is used.”
Regression and Kriging metamodels with their experimental designs in simulation: A review (2017, background): “pplications of jackknifing in simulation are numerous; see Gordy nd Juneja (2010) and Kleijnen (2015 , p.”
A Single-Loop Kriging Surrogate Modeling for Time-Dependent Reliability Analysis (2016, unknown): “where r x ð Þ 1⁄4 R x; x1 ð Þ; R x; x2 ð Þ; ; R x; xns ð Þ The mean square error of the prediction is given by [37]”
DiceKriging, DiceOptim: Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization (2012, methodology): “Alternatively, MATLAB toolboxes emanating from the computer experiments community have become popular among practitioners, like MPerK (Santner et al. 2003) and DACE (Lophaven, Nielsen, and Sondergaard 2002), or GPML (Rasmussen and Nickisch, 2011; Rasmussen and Williams, 2006b) in the context of Gaus”
A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models (2013, methodology): “It is consequently very easily implementable with standard Kriging toolboxes such as DACE toolbox [30].”
Kriging metamodeling in simulation: A review (2009, unknown): “For the estimation of the correlation functions and the optimal weights through (12), I recommend the Matlab Kriging toolbox DACE, which is free of charge; see [15].”
Development and evaluation of gappy-POD as a data reconstruction technique for noisy PIV measurements in gas turbine combustors (2016, methodology): “In this work, Kriging interpolation was implemented in MATLAB using the DACE toolbox, a more in depth mathematical description of the technique can be found in Lophaven et al (2002).”
Hierarchical Kriging Model for Variable-Fidelity Surrogate Modeling (2012, methodology): “In this article, a cubic spline correlation function [35] is employed as it is nearly as good as the Gaussian exponential function but always second-order differentiable, which is a desired featurewhen gradient information is to be incorporated.”