@incollection{eprints1444,
          author = {Gabriella Dellino and Carlo Meloni},
            note = {Article No.: 334},
       publisher = {ACM},
           month = {December},
            year = {2012},
           title = {Metamodel variability analysis combining bootstrapping and validation techniques},
       booktitle = {WSC '12 Proceedings of the Winter Simulation Conference },
             url = {http://eprints.imtlucca.it/1444/},
        abstract = {Research on metamodel-based optimization has received considerably increasing interest in recent years, and has found successful applications in solving computationally expensive problems. The joint use of computer simulation experiments and metamodels introduces a source of uncertainty that we refer to as metamodel variability. To analyze and quantify this variability, we apply bootstrapping to residuals derived as prediction errors computed from cross-validation. The proposed method can be used with different types of metamodels, especially when limited knowledge on parameters? distribution is available or when a limited computational budget is allowed. Our preliminary experiments based on the robust version of
the EOQ model show encouraging results.}
}