Nonlinear regression with autocorrelated errors

A. Ronald Gallant, J. Jeffery Goebel

Research output: Contribution to journalArticlepeer-review

109 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)961-967
Number of pages7
JournalJournal of the American Statistical Association
Volume71
Issue number356
DOIs
StatePublished - Dec 1976

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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