@prefix dcat: . @prefix dct: . @prefix foaf: . @prefix vcard: . @prefix xsd: . a dcat:Dataset ; dct:description """ In many practical cases, a sensitivity analysis or an optimization of a complex time consuming computer code requires to build a fast running approximation of it - also called surrogate model. We consider in this paper the problem of building a surrogate model of a complex computer code which can be run at different levels of accuracy. The co-kriging based surrogate model is a promising tool to build such an approximation. The idea is to improve the surrogate model by using fast and less accurate versions of the code. We present here a new approach to perform a multi-fidelity co-kriging model which is based on a recursive formulation. The strength of this new method is that the co-kriging model is built through a series of independent kriging models. From them, some properties of classical kriging models can naturally be extended to the presented co-kriging model such as a fast cross-validation procedure. Moreover, based on a Bayes linear formulation, an extension of the universal kriging equations are provided for the co-kriging model. Finally, the proposed model has the advantage to reduce the computational complexity compared to the previous models. The multi-fidelity model is successfully applied to emulate a hydrodynamic simulator. This real example illustrates the efficiency of the recursive model. """ ; dct:identifier "hal-00737332" ; dct:issued "2026-05-15T10:29:23.307627"^^xsd:dateTime ; dct:language "en" ; dct:modified "2026-05-15T10:29:23.307633"^^xsd:dateTime ; dct:publisher ; dct:title "Recursive co-kriging model for Design of Computer experiments with multiple levels of fidelity with an application to hydrodynamic" ; dcat:contactPoint [ a vcard:Organization ; vcard:fn "CCSD" ] ; dcat:distribution ; dcat:keyword "fast-cross-validation", "infoeu-reposemanticspreprint", "mathmath-stmathematics-mathstatistics-mathst", "multi-fidelity-computer-code", "preprints-working-papers-", "recursive-model", "statthstatistics-statstatistics-theory-statth", "surrogate-models", "universal-co-kriging" ; dcat:landingPage . a dcat:Distribution ; dct:format "HTML" ; dct:issued "2026-05-15T10:29:23.325518"^^xsd:dateTime ; dct:modified "2026-05-15T10:29:23.287768"^^xsd:dateTime ; dct:title "Recursive co-kriging model for Design of Computer experiments with multiple levels of fidelity with an application to hydrodynamic" ; dcat:accessURL . a foaf:Agent ; foaf:name "test_moissonnage_selune" . a foaf:Document .