## Nonlinear Full Information Maximum Likelihood Estimator

In this subsection we shall consider the maximum likelihood estimator of model (8.2.1) under the normality assumption of uu. To do so we must assume that (8.2.1) defines a one-to-one correspondence between y, and uf. This assumption enables us to write down the likelihood function in the usual way as the product of the density of u, and the Jacobian. Unfortunately, this is a rather stringent assumption, which considerably limits the usefulness of the nonlinear full information maximum likelihood (NLFI) estimator in practice. There are two types of problems: (1) There may be no solution for у for some values of u. (2) There may be more than one solution for у for some values of u...

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