Single-experiment input uncertainty

Y. Lin, E. Song, B. L. Nelson

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


'Input uncertainty' refers to the simulation model risk caused by estimating input distributions from real-world data, and specifically the (usually unmeasured) variance in performance estimates that this introduces. We provide the first single-run method for quantifying input uncertainty, meaning that we derive our measure of input-uncertainty variance - both overall variance and the contribution to it of each input model - from the nominal experiment that the analyst would typically run using the estimated input models; other methods in the literature require additional diagnostic experiments. Application of our method is illustrated with two examples.

Original languageEnglish (US)
Pages (from-to)249-259
Number of pages11
JournalJournal of Simulation
Issue number3
StatePublished - Aug 16 2015

All Science Journal Classification (ASJC) codes

  • Software
  • Modeling and Simulation
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering


Dive into the research topics of 'Single-experiment input uncertainty'. Together they form a unique fingerprint.

Cite this