Examining robustness of model selection with halfnormal 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 halfnormal 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 halfnormal 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):
 LAUR1629402
Journal ID: ISSN 07488017
 Grant/Contract Number:
 AC5206NA25396
 Type:
 Accepted Manuscript
 Journal Name:
 Quality and Reliability Engineering International
 Additional Journal Information:
 Journal Volume: 33; Journal Issue: 8; Journal ID: ISSN 07488017
 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; halfnormal plot; important effects; LASSO influence plot; LASSO plot; least absolute shrinkage and selection operation
 OSTI Identifier:
 1375170
Jang, Dae Heung, and AndersonCook, Christine Michaela. Examining robustness of model selection with halfnormal and LASSO plots for unreplicated factorial designs. United States: N. p.,
Web. doi:10.1002/qre.2156.
Jang, Dae Heung, & AndersonCook, Christine Michaela. Examining robustness of model selection with halfnormal and LASSO plots for unreplicated factorial designs. United States. doi:10.1002/qre.2156.
Jang, Dae Heung, and AndersonCook, Christine Michaela. 2017.
"Examining robustness of model selection with halfnormal 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 halfnormal and LASSO plots for unreplicated factorial designs},
author = {Jang, Dae Heung and AndersonCook, 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 halfnormal 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 halfnormal 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}
}