Representing and generating uncertainty effectively

  • Kelton W
  • 18


    Mendeley users who have this article in their library.
  • 3


    Citations of this article.


Stochastic simulations involve at least some random inputs. This introductory tutorial is meant to call attention to the need to model and generate such inputs in ways that may not be the standard or defaults in simulation-modeling software. There are both dangers involved with doing things inappropriately, as well as opportunities to do things better, making for more accurate and more precise results from simulations. Specific issues include possible dependence across and within random inputs, use of empirical distributions, and non-default use of the underlying random-number generator. Suggestions for novel ways of implementing some of these ideas in simulation-modeling software are offered.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document


  • W. David Kelton

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free