Berry-Esseen bounds of weighted kernel estimator for a nonparametric regression model based on linear process errors under a LNQD sequence
نویسندگان
چکیده
In this paper, the authors investigate the Berry-Esseen bounds of weighted kernel estimator for a nonparametric regression model based on linear process errors under a LNQD random variable sequence. The rate of the normal approximation is shown as [Formula: see text] under some appropriate conditions. The results obtained in the article generalize or improve the corresponding ones for mixing dependent sequences in some sense.
منابع مشابه
A Berry-Esseen Type Bound for a Smoothed Version of Grenander Estimator
In various statistical model, such as density estimation and estimation of regression curves or hazard rates, monotonicity constraints can arise naturally. A frequently encountered problem in nonparametric statistics is to estimate a monotone density function f on a compact interval. A known estimator for density function of f under the restriction that f is decreasing, is Grenander estimator, ...
متن کاملBerry-Esseen bounds for wavelet estimator in semiparametric regression model with linear process errors
* Correspondence: lym1019@163. com Department of Mathematics, Shangrao Normal University, Shangrao 334001, China Full list of author information is available at the end of the article Abstract Consider the semiparametric regression model Yi = xi b + g (ti) + εi, i = 1, . . . , n, where the linear process errors εi = ∑∞ j=−∞ ajei−j with ∑∞ j=−∞ ∣∣aj∣∣ < ∞ , and {ei} are identically distributed a...
متن کاملThe Berry-Esseen bounds of wavelet estimator for regression model whose errors form a linear process with a ρ-mixing
*Correspondence: [email protected] 1School of Information and Statistics, Guangxi University of Finance and Economics, Nanning, 530003, P.R. China Full list of author information is available at the end of the article Abstract In this paper, considering the nonparametric regression model Yni = g(ti) + εi (1≤ i≤ n), where εi =∑∞j=–∞ ajei–j and ei–j are identically distributed and ρ-mixing s...
متن کاملA Berry-Esseen Type Bound for the Kernel Density Estimator of Length-Biased Data
Length-biased data are widely seen in applications. They are mostly applicable in epidemiological studies or survival analysis in medical researches. Here we aim to propose a Berry-Esseen type bound for the kernel density estimator of this kind of data.The rate of normal convergence in the proposed Berry-Esseen type theorem is shown to be O(n^(-1/6) ) modulo logarithmic term as n tends to infin...
متن کاملKernel Ridge Estimator for the Partially Linear Model under Right-Censored Data
Objective: This paper aims to introduce a modified kernel-type ridge estimator for partially linear models under randomly-right censored data. Such models include two main issues that need to be solved: multi-collinearity and censorship. To address these issues, we improved the kernel estimator based on synthetic data transformation and kNN imputation techniques. The key idea of this paper is t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره 2018 شماره
صفحات -
تاریخ انتشار 2018