Robust estimation of nonlinear regression with autoregressive errors
Generalized M (or GM) estimation has been extended to the case of a nonlinear regression model with autoregressive and heteroscedastic errors. The robustness properties of the GM estimators have been investigated based on the time-series analog of Hampel's influence function. The asymptotic properties of these estimators have been studied in some detail.
Year of publication: |
2003
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Authors: | Sinha, Sanjoy K. ; Field, Christopher A. ; Smith, Bruce |
Published in: |
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 63.2003, 1, p. 49-59
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Publisher: |
Elsevier |
Keywords: | Nonlinear regression Autoregressive errors Generalized M estimation Influence function Asymptotic normality Mixing |
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