Complete Consistency For Estimator Research Articles

Complete f-moment convergence for m-asymptotic negatively associated random variables and related statistical applications

In this article, the complete f-moment convergence for m-asymptotic negatively associated random variables is investigated. As applications, we establish the strong consistency of the least square estimator in the simple linear errors-in-variables models and the complete consistency for estimator in the semiparametric regression model based on m-asymptotic negatively associated errors. We also give some simulations to assess the finite sample performance of the theoretical results.

Limit behaviors of the estimator of non parametric regression model based on extended negatively dependent errors

In this article, we study the complete consistency for the estimator of non parametric regression model based on extended negatively dependent errors, and obtain the convergence rates of the complete consistency by using the inequalities for extended negatively dependent random variables. As an application, the complete consistency and convergence rate for the nearest neighbor estimator are obtained. Finally, some simulations are illustrated.

On Complete Consistency for the Estimator of Nonparametric Regression Model Based on Asymptotically Almost Negatively Associated Errors

In this paper, we mainly study the consistency for the estimator of nonparametric regression model based on asymptotically almost negatively associated (AANA, in short) errors. Firstly, the Bernstein type inequality for AANA random variables is established. By using the Bernstein type inequality and moment inequalities, we investigate the complete consistency and convergence rate for the estimator of nonparametric regression model based on AANA errors. As applications, the complete consistency and convergence rate for the nearest neighbor estimator are obtained.