Validating the Assumptions of Sequential Bifurcation in Factor Screening

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Abstract

Sequential bifurcation (SB) is a very efficient and effective method for identifying the important factors (inputs) of simulation models with very many factors, provided the SB assumptions are valid. A variant of SB called multiresponse SB (MSB) can be applied to simulation models with multiple types of responses (outputs). The specific SB and MSB assumptions are: (i) a second-order
polynomial per output is an adequate approximation (valid metamodel) of the implicit input/output function of the underlying simulation model; (ii) the directions (signs) of the first-order effects are known (so the first-order polynomial approximation per output is monotonic); (iii) heredity applies; i.e., if an input has no important first-order effect, then this input has no important second-order effects. To validate these three assumptions, we develop new methods. We compare these methods through Monte Carlo experiments and a case study.
Original languageEnglish
Place of PublicationTilburg
PublisherCentER, Center for Economic Research
Number of pages32
Volume2015-034
Publication statusPublished - 17 Jun 2015

Publication series

NameCentER Discussion Paper
Volume2015-034

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Keywords

  • simulation
  • sensitivity analysis
  • Design of experiments
  • statistical analysis

Cite this

Shi, W., & Kleijnen, J. P. C. (2015). Validating the Assumptions of Sequential Bifurcation in Factor Screening. (CentER Discussion Paper; Vol. 2015-034). Tilburg: CentER, Center for Economic Research.