### 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.

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 language | English |
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Place of Publication | Tilburg |

Publisher | CentER, Center for Economic Research |

Number of pages | 32 |

Volume | 2015-034 |

Publication status | Published - 17 Jun 2015 |

### Publication series

Name | CentER Discussion Paper |
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Volume | 2015-034 |

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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.