Nonlinear Regression with Autocorrelated Error

(in Theory and Methods)

Nonlinear Regression with Autocorrelated Errors

A. Ronald Gallant, J. Jeffery Goebel

Journal of the American Statistical Association, Vol. 71, No. 356. (Dec., 1976), pp. 961-967.

Abstract

An estimator of the parameters of a nonlinear time series regression is obtained by using an autoregressive assumption to approximate the variance-covariance matrix of the disturbances. Considerations are set forth which suggest that this estimator will have better small sample efficiency than circular estimators. Such is the case for examples considered in a Monte Carlo study.