Abstract
This chapter is devoted to model checking procedures. Without having validated the assumptions underlying a nonlinear regression model, we cannot be sure that the model is appropriate and consequently that the conclusions based upon the model fit are correct. The kinship to linear regression is apparent, as many of the techniques applicable for linear regression are also useful for nonlinear regression.
If any model violations are found, then Chapter 6 should be consulted.
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© 2009 Springer-Verlag Berlin Heidelberg
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(2009). Model Diagnostics. In: Ritz, C., Streibig, J.C. (eds) Nonlinear Regression with R. Use R. Springer, New York, NY. https://doi.org/10.1007/978-0-387-09616-2_5
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DOI: https://doi.org/10.1007/978-0-387-09616-2_5
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-09615-5
Online ISBN: 978-0-387-09616-2
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