This analysis demonstrates complete consistency of the G-M estimator in nonparametric regression, indicating broad applicability in statistical modeling.
In this paper, we study the complete consistency of the G-M estimator in a nonparametric regression model based on extended negatively dependent errors, and we obtain the convergence rates of the complete consistency by using the inequalities for extended negatively dependent random variables. Finally, some simulations are illustrated.
No takes yet. Share an insight, caveat, or question.
Qu et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: