DocumentCode :
3381673
Title :
Simulation statistical software: an introspective appraisal
Author :
Sanchez, Paul J. ; Chance, Frank ; Healy, Kevin J. ; Henriksen, James O. ; Kelton, David W. ; Vincent, Stephen G.
Author_Institution :
Indalo Software, St. Louis, MO, USA
fYear :
1994
fDate :
11-14 Dec. 1994
Firstpage :
1311
Lastpage :
1315
Abstract :
Simulation experiments are sampling experiments by their very nature. Statistical issues dominate all aspects of a well-designed simulation study-model validation, selection of input distributions and associated parameters, experiment design frameworks, output analysis methodologies, model sensitivity, and forecasting are examples of some of the issues which must be dealt with by simulation experimenters. There are many factors which complicate analyses, such as multivariate input distributions, serially correlated model inputs and outputs, multiple performance measures, and non-linear system response, to name a few. The purpose of this panel is to discuss any and all issues related to software tools available for dealing with these and other problems. I asked five experts from within the simulation community to share their opinions and insights on the availability and quality of software to meet the statistical needs of the simulation community. The position statements provided by them are intended to serve as a springboard for a more extensive exchange of ideas during the discussion at the conference.
Keywords :
digital simulation; software quality; software tools; statistical analysis; experiment design; forecasting; input distributions; model sensitivity; model validation; multiple performance measures; multivariate input distributions; nonlinear system response; output analysis methodologies; sampling experiments; serially correlated model inputs; simulation statistical software; software quality; software tools; well-designed simulation study; Analytical models; Appraisal; Engineering management; Etching; Industrial engineering; Packaging; Predictive models; Rivers; Sampling methods; Steady-state;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Simulation Conference Proceedings, 1994. Winter
Print_ISBN :
0-7803-2109-X
Type :
conf
DOI :
10.1109/WSC.1994.717524
Filename :
717524
Link To Document :
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