(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.
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.