Robust Design Strategies for Nonlinear Regression Models
نویسنده
چکیده
In the context of nonlinear regression models, this paper outlines recent de velopments in design strategies when the assumed model function, initial parameter guesses, and/or error structure are not known with complete certainty. Designs obtained using these strategies are termed robust de signs as they are intended to be robust to specified departures. Robust designs are clearly advantageous in many practical settings since these de signs can be used to test for, say, lack of fit ofthe assumed model function or error heteroskedasticity, whereas so-called optimal designs often cannot.
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