Consistency for the least squares estimator in nonlinear regression model

Hu Shuhe

Statistics & Probability Letters, 2004, vol. 67, issue 2, 183-192

Abstract: The consistency problems of the least-squares estimator [theta]n for parameter [theta] in nonlinear regression model are resolved perfectly. Assuming that the tth absolute moments of the model errors are finite, for t[greater-or-equal, slanted]2 and the errors satisfy general dependent conditions, we obtain the same probability inequality as that in Ivanov (Theory Probab. Appl. 21 (1976) 557) which has independent identically distributed errors; for 1

Keywords: Nonlinear; regression; model; Least-squares; estimator; Dependent; error; Consistency; Consistency; rate (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (3)

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