Nonlinear regression with dependent observations. (English) Zbl 0533.62055
The authors establish general conditions for consistency and asymptotic normality for the nonlinear least squares estimators. These results are based on the extensions of the law of large numbers and the central limit theorem for random processes with mixing conditions. New tests for model misspecification based on the information matrix testing principle are also given.
Reviewer: A.Novikov
MSC:
62J02 | General nonlinear regression |
62P20 | Applications of statistics to economics |
60G10 | Stationary stochastic processes |