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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… Click to show full 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:
regression;
deviation results;
regression model;
large deviation;
dependent errors;
nonlinear regression
Journal Title: TEST
Year Published: 2017
Link to full text (if available)
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Journal Title: TEST
Year Published: 2017
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!