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Response Surfaces: Designs and Analyses
Abstract
Introduction to response surface methodology matrix algebra, least squares, the analysis of variance, and principles of experimental design first-order models and designs second-order models and designs determining optimum conditions methods of estimating response surfaces that rival least squares based on the integrated mean squared error criterion analysis of multiresponse experiments response surface models with block effects mixture designs and analyses nonlinear response surface models Taguchi's robust parameter design additional topics and some directions for future research. Appendix: solutions to selected exercises.
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Citations
Cited by
Pignatello, J. J., Oliveros, E., & MacKay, A. (2006) · Critical Reviews in Environmental Science and Technology · doi:10.1080/10643380500326564 · Cited by 4,133
Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems
Helton, J. C., & Davis, F. J. (2003) · Reliability Engineering & System Safety · doi:10.1016/s0951-8320(03)00058-9 · Cited by 2,688
Ghafari, S., Aziz, H. A., Isa, M. H., & Zinatizadeh, A. A. (2009) · Journal of Hazardous Materials · doi:10.1016/j.jhazmat.2008.07.090 · Cited by 623
Designing Environmental Field Studies
Eberhardt, L. L., & Thomas, J. M. (1991) · Ecological Monographs · doi:10.2307/1942999 · Cited by 455
Amini, M., Younesi, H., Bahramifar, N., Lorestani, A. A. Z., Ghorbani, F., Daneshi, A., & Sharifzadeh, M. (2008) · Journal of Hazardous Materials · doi:10.1016/j.jhazmat.2007.10.114 · Cited by 444
Metadata
- Authors
- Ziegel, E. R.
- Venue
- Technometrics
- Publisher
- Informa UK Limited
- Published
- 1997-08
- Volume
- 39
- Issue
- 3
- Pages
- 342-342
- ISSN
- 0040-1706 (ISSN-L)
- 1537-2723
- OpenAlex
- W2055180707
- Cited by
- 1,520
- References
- 0
- FWCI
- 60.38
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
