Biedermann, S. and Woods, D.C. "Optimal designs for generalized nonlinear models with application to second harmonic generation experiments." Journal of the Royal Statistical Society, Series C. 60.2 (2011): 281-299. Electronic.
The paper extends the theoretical basis for non-linear regression using Bayesian design to cluster design. For experiments where the errors are not believed to be normally distributed, non-linear parametric regression models are needed to "describe the influence of one or more explanatory variables on a response." More specifically, "Generalized non-linear models extend non-linear regression models to allow non-normally distributed error structures." After formulating the procedure, the authors use various tests to determine the robustness of GNM (generalized non-linear models).
This article outlines the mathematical and practical tests statisticians use in determining properties of new theories. If my project tends to the more theoretical side, this provides a wonderful basis for usual tests.
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