The large deviation results for the nonlinear regression model with dependent errors

Wenzhi Yang (), Zhangrui Zhao (), Xinghui Wang () and Shuhe Hu ()
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Wenzhi Yang: Anhui University
Zhangrui Zhao: Anhui University
Xinghui Wang: Anhui University
Shuhe Hu: Anhui University

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2017, vol. 26, issue 2, No 2, 283 pages

Abstract: Abstract In this paper, we investigate the least squares (LS) estimator of the nonlinear regression model based on the extended negatively dependent errors which are widely dependent structures. Under the general conditions, we establish some large deviation results for the LS estimator of the nonlinear regression parameter, which can be applied to obtain a weak uniform consistency and a complete convergence rate for this estimator. In addition, some examples and simulations are presented for illustration.

Keywords: Large deviation; Nonlinear regression models; Least squares estimator; END random variables; 62J02; 62F12 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11749-016-0509-z

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