@inproceedings{69af4a038cfc4747852e1af6717ecffc,
title = "Estimating Sensitivity to Input Model Variance",
abstract = "Simple question: How sensitive is your simulation output to the variance of your simulation input models? Unfortunately, the answer is not simple because the variance of many standard parametric input distributions can achieve the same change in multiple ways as a function of the parameters. In this paper we propose a family of output-mean-with-respect-to-input-variance sensitivity measures and identify two particularly useful members of it. A further benefit of this family is that there is a straightforward estimator of any member with no additional simulation effort beyond the nominal experiment. A numerical example is provided to illustrate the method and interpretation of results.",
author = "Jiang, {Wendy Xi} and Nelson, {Barry L.} and Hong, {L. Jeff}",
note = "Funding Information: This work was supported by National Science Foundation Grant Number CMMI-1634982. Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 Winter Simulation Conference, WSC 2019 ; Conference date: 08-12-2019 Through 11-12-2019",
year = "2019",
month = dec,
doi = "10.1109/WSC40007.2019.9004684",
language = "English (US)",
series = "Proceedings - Winter Simulation Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3705--3716",
booktitle = "2019 Winter Simulation Conference, WSC 2019",
address = "United States",
}