an:03846684
Zbl 0533.62055
White, Halbert; Domowitz, Ian
Nonlinear regression with dependent observations
EN
Econometrica 52, 143-161 (1984).
0012-9682 1468-0262
1984
j
62J02 62P20 60G10
dependent observations; new covariance matrix estimator; new tests for model misspecification; consistency; asymptotic normality; nonlinear least squares estimators; extensions of the law of large numbers; central limit theorem; random processes with mixing conditions; information matrix testing principle
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.
A.Novikov