Selection of active effects based on a ridge regression in supersaturated response surface designs
Author:
Affiliation:
1. Keio University
2. Yokohama Plant, NISSAN MOTOR CO.,LTD.
Publisher
The Japanese Society for Quality Control
Link
https://www.jstage.jst.go.jp/article/tqs/2/1/2_1/_pdf
Reference42 articles.
1. 1) Abraham, B., Chipman, H., and Vijayan K. (1999), “Some risks in the construction and analysis of supersaturated designs”, Technometrics, Vol. 41, No. 2, pp. 135-141.
2. 2) Allen, T. T. and Bernshteyn, M., (2003), “Supersaturated designs that maximize the probability of identifying active factors”, Technometrics, Vol. 45, No. 1, pp. 90-97.
3. 3) Anderson-Cook, C. M., Borror, C. M., and Montgomery, D. C. (2009), “Response surface design evaluation and comparison”, Journal of Statistical Planning and Inference, Vol. 139, No. 2, pp. 629-641.
4. 4) Androulakis, E., Angelopoulos, P., and Koukouvinos, C. (2013), “A comparison of three-level orthogonal arrays in the presence of different correlation structures in observations”, Communications in Statistics - Simulation and Computation, Vol. 42, No. 3, pp. 552-569.
5. 5) Beattie, S. D., Fong, D. K. H., and Lin, D. K. J. (2002), “A two-stage Bayesian model selection strategy for supersaturated designs”, Technometrics, Vol. 44, No. 1, pp. 55-63.
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