ABSTRACT
Until now the focus has been on linear models where the mean of the outcome (or possibly a transformation of the response) is a linear function of the unknown parameters from the statistical model. In this chapter we consider the more general class of non-linear regression models, where some of the parameters in the model do not have a linear relationship with the mean response. Yet the aims of the analysis are the same: estimation of the parameters from the non-linear functional relationship and quantification of the uncertainty of the parameters so it is possible to create confidence intervals and test hypotheses.
