Factor Screening in Simulation: Evaluation of Two Strategies Based on Random Balance Sampling
AbstractIn the study of large, complex computer simulation models the user is often overwhelmed by the vast number of input variables. Moreover, he or she is usually confused about how to make an effective analysis of the model without performing an excessive number of runs, which tend to be costly and time consuming. Factor screening methods, which attempt to identify the more important variables, can be extremely useful in the study of such models. This paper presents and evaluates two screening strategies based upon random balance sampling. Both strategies are applicable when there are more variables to be screened than there are available screening runs. The results provide guidance in using these strategies in particular screening applications.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by INFORMS in its journal Management Science.
Volume (Year): 30 (1984)
Issue (Month): 2 (February)
factor screening; computer simulation; simulation methodology; random balance sampling; statistical techniques in simulation;
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc).
If references are entirely missing, you can add them using this form.