Abstract
AbstractThe purpose of this paper is twofold: (1) We establish the consistency of the least‐squares estimator in a nonlinear modelyi = f(xi,θ) +σiei where the range of the parameter θ is noncompact, the regression function is unbounded, and the σi,'s are not necessarily equal. This extends the results in Jennrich (1969) and Wu (1981). (2) Under the same model, the jackknife estimator of the asymptotic covariance matrix of the least‐squares estimator is shown to be consistent, which provides a theoretical justification of the empirical results in Duncan (1978) and the use of the jackknife method in large‐sample inferences.
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