Sequential group Morris method with error control for efficient factor screening in simulation experiments

Wen Shi

doi:10.1080/24725854.2026.2641685

Sequential group Morris method with error control for efficient factor screening in simulation experiments

2026-03-01

0

PRE

AI

DOI：10.1080/24725854.2026.2641685

Original

Original request for help

Save

Abstract

En 中文

The Morris elementary effects method (MM) is a widely used, model-free approach for factor screening and sensitivity analysis across various domains. However, traditional MM can be computationally demanding due to its one-factor-at-a-time nature. This paper presents a novel multi-stage sequential-group Morris method (SGMM) and a corresponding sequential implementation procedure tailored for both deterministic and stochastic simulation settings. SGMM leverages prior knowledge of the directional influence of individual factors to define elementary effects at the group level. This enables early elimination of factor groups with negligible group effects. Each stage employs a distribution-free sequential probability ratio test (SPRT) to evaluate the significance of group effects, ensuring rigorous control over Type I and Type II familywise error rates. Numerical experiments show that SGMM consistently outperforms existing simulation-based factor screening methods, delivering up to 87.87% computational savings while preserving high statistical accuracy.

Keywords:

Simulation experiments

factor screening

distribution-free

sequential probability ratio test

Sequential group Morris method with error control for efficient factor screening in simulation experiments

Abstract

Journal

Organization