Examining robustness of model selection with half-normal and LASSO plots for unreplicated factorial designs
When there are constraints on resources, an unreplicated factorial or fractional factorial design can allow efficient exploration of numerous factor and interaction effects. A half-normal plot is a common graphical tool used to compare the relative magnitude of effects and to identify important effects from these experiments when no estimate of error from the experiment is available. An alternative is to use a least absolute shrinkage and selection operation plot to examine the pattern of model selection terms from an experiment. We examine how both the half-normal and least absolute shrinkage and selection operation plots are impacted by the absence of individual observations or an outlier, and the robustness of conclusions obtained from these 2 techniques for identifying important effects from factorial experiments. As a result, the methods are illustrated with 2 examples from the literature.
- Authors:
-
[1]
;
[2]
- Pukyong National Univ., Busan (South Korea)
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Publication Date:
- Report Number(s):
- LA-UR-16-29402
Journal ID: ISSN 0748-8017
- Grant/Contract Number:
- AC52-06NA25396
- Type:
- Accepted Manuscript
- Journal Name:
- Quality and Reliability Engineering International
- Additional Journal Information:
- Journal Volume: 33; Journal Issue: 8; Journal ID: ISSN 0748-8017
- Publisher:
- Wiley
- Research Org:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Org:
- USDOD; USDOE
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING; Mathematics; half-normal plot; important effects; LASSO influence plot; LASSO plot; least absolute shrinkage and selection operation
- OSTI Identifier:
- 1375170
Jang, Dae -Heung, and Anderson-Cook, Christine Michaela. Examining robustness of model selection with half-normal and LASSO plots for unreplicated factorial designs. United States: N. p.,
Web. doi:10.1002/qre.2156.
Jang, Dae -Heung, & Anderson-Cook, Christine Michaela. Examining robustness of model selection with half-normal and LASSO plots for unreplicated factorial designs. United States. doi:10.1002/qre.2156.
Jang, Dae -Heung, and Anderson-Cook, Christine Michaela. 2017.
"Examining robustness of model selection with half-normal and LASSO plots for unreplicated factorial designs". United States.
doi:10.1002/qre.2156. https://www.osti.gov/servlets/purl/1375170.
@article{osti_1375170,
title = {Examining robustness of model selection with half-normal and LASSO plots for unreplicated factorial designs},
author = {Jang, Dae -Heung and Anderson-Cook, Christine Michaela},
abstractNote = {When there are constraints on resources, an unreplicated factorial or fractional factorial design can allow efficient exploration of numerous factor and interaction effects. A half-normal plot is a common graphical tool used to compare the relative magnitude of effects and to identify important effects from these experiments when no estimate of error from the experiment is available. An alternative is to use a least absolute shrinkage and selection operation plot to examine the pattern of model selection terms from an experiment. We examine how both the half-normal and least absolute shrinkage and selection operation plots are impacted by the absence of individual observations or an outlier, and the robustness of conclusions obtained from these 2 techniques for identifying important effects from factorial experiments. As a result, the methods are illustrated with 2 examples from the literature.},
doi = {10.1002/qre.2156},
journal = {Quality and Reliability Engineering International},
number = 8,
volume = 33,
place = {United States},
year = {2017},
month = {4}
}
- Free Publicly Accessible Full Text
-
Accepted Manuscript (DOE)
- Publisher's Version of Record
- https://doi.org/10.1002/qre.2156