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Input screening: Finding the important model inputs on a budget

Author

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  • Morris, Max D.

Abstract

One general goal of sensitivity or uncertainty analysis of a computer model is the determination of which inputs most influence the outputs of interest. Simple methodologies based on randomly sampled input values are attractive because they require few assumptions about the nature of the model. However, when the number of inputs is large and the computational effort required per model evaluation is significant, methods based on more complex assumptions, analysis techniques, and/or sampling plans may be preferable. This paper will review some approaches that have been proposed for input screening, with an emphasis on the balance between assumptions and the number of model evaluations required.

Suggested Citation

  • Morris, Max D., 2006. "Input screening: Finding the important model inputs on a budget," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1252-1256.
    • Handle: RePEc:eee:reensy:v:91:y:2006:i:10:p:1252-1256
    DOI: 10.1016/j.ress.2005.11.022
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    Citations

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    Cited by:

    1. Wen Shi & Xi Chen & Jennifer Shang, 2019. "An Efficient Morris Method-Based Framework for Simulation Factor Screening," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 745-770, October.
    2. Shi, Wen & Zhou, Qing & Zhou, Yanju, 2023. "An efficient elementary effect-based method for sensitivity analysis in identifying main and two-factor interaction effects," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    3. Shi, Wen & Chen, Xi, 2019. "Controlled Morris method: A new factor screening approach empowered by a distribution-free sequential multiple testing procedure," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 299-314.
    4. Wen Shi & Xi Chen, 2018. "Efficient budget allocation strategies for elementary effects method in stochastic simulation," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(3), pages 218-241, April.

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