Nonlinear Statistical Models

Specifically, we discussed estimation of the model parameters, measurements of uncertainty in these estimates and the predicted values, and the use of confidence intervals or significance tests to assess the significance of parameters. Through the matrix formulation, we essentially saw that in linear models (where the model is a linear function of the parameters), the estimates of linear functions of the response values, and the standard errors of these estimates have simple closed-form expressions and can thus be analytically computed. Unfortunately, this will not be the case for nonlinear models.