Abstract
The consistency problems of the least-squares estimator θ n for parameter θ in nonlinear regression model are resolved perfectly. Assuming that the tth absolute moments of the model errors are finite, for t⩾2 and the errors satisfy general dependent conditions, we obtain the same probability inequality as that in Ivanov (Theory Probab. Appl. 21 (1976) 557) which has independent identically distributed errors; for 1< t<2, we first obtain weak consistency and weak consistency rate of θ n .
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