Abstract
Thin plate splines and kriging models are proposed as methods for approximating unknown response functions in the context of process optimization. Connections between the methods are discussed and implementation of the models using S-PLUS is described. Results are presented from a simulation study comparing the methods and further necessary work is identified.
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© 1995 Springer Science+Business Media New York
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O’Connell, M., Haaland, P., Hardy, S., Nychka, D. (1995). Nonparametric Regression, Kriging and Process Optimization. In: Seeber, G.U.H., Francis, B.J., Hatzinger, R., Steckel-Berger, G. (eds) Statistical Modelling. Lecture Notes in Statistics, vol 104. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-0789-4_26
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DOI: https://doi.org/10.1007/978-1-4612-0789-4_26
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-94565-1
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