Zimmermann, R. On the maximum likelihood training of gradient-enhanced spatial Gaussian processes. (English) Zbl 1283.62201 SIAM J. Sci. Comput. 35, No. 6, A2554-A2574 (2013). Cited in 3 Documents MSC: 62M30 Inference from spatial processes 62P30 Applications of statistics in engineering and industry; control charts 65C60 Computational problems in statistics (MSC2010) 62M20 Inference from stochastic processes and prediction 65C20 Probabilistic models, generic numerical methods in probability and statistics Keywords:design and analysis of computer experiments; gradient-enhanced Kriging; spatial linear models; response surface; surrogate model; hyper-parameter training; maximum likelihood Software:DACE; Matlab; TAU PDF BibTeX XML Cite \textit{R. Zimmermann}, SIAM J. Sci. Comput. 35, No. 6, A2554--A2574 (2013; Zbl 1283.62201) Full Text: DOI