The asymptotic normality of the linear weighted estimator in nonparametric regression models
From MaRDI portal
Publication:5078423
DOI10.1080/03610926.2018.1429633OpenAlexW2792861735MaRDI QIDQ5078423
Aiting Shen, Caoqing Wu, Mingming Ning
Publication date: 23 May 2022
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2018.1429633
asymptotic normalitynonparametric regression model\(\rho\)-mixing random variableslinear weighted estimator
Related Items (3)
Complete consistency for the estimator of nonparametric regression model based on martingale difference errors ⋮ Complete consistency for the estimator of nonparametric regression model based on \(m\)-END errors ⋮ Limit behaviors of the estimator of non parametric regression model based on extended negatively dependent errors
Cites Work
- Unnamed Item
- The Berry-Esseen bounds of wavelet estimator for regression model whose errors form a linear process with a \(\rho\)-mixing
- Bernstein-type inequality for weakly dependent sequence and its applications
- The consistency for estimator of nonparametric regression model based on NOD errors
- Some inequalities for a LNQD sequence with applications
- On moments of the maximum of normed partial sums of \(\rho \)-mixing random variables
- Chover-type laws of the \(k\)-iterated logarithm for \(\tilde {\rho }\)-mixing sequences of random variables
- Weak and universal consistency of moving weighted averages
- Nonparametric function recovering from noisy observations
- An invariance principle for \(\phi\)-mixing sequences
- Consistent nonparametric multiple regression: the fixed design case
- Fixed design regression for time series: Asymptotic normality
- Consistent nonparametric regression. Discussion
- Weak convergence of multidimensional empirical processes for stationary \(\varphi\)-mixing processes
- Maximal inequalities for partial sums of \(\rho\)-mixing sequences
- Some Baum-Katz type results for \({\varphi}\)-mixing random variables with different distributions
- Bernstein-type inequality for widely dependent sequence and its application to nonparametric regression models
- Complete moment convergence for weighted sums of weakly dependent random variables and its application in nonparametric regression model
- On complete convergence for widely orthant-dependent random variables and its applications in nonparametric regression models
- Asymptotic properties for estimates of nonparametric regression models based on negatively associated sequences
- Asymptotic properties of wavelet-based estimator in nonparametric regression model with weakly dependent processes
- Maximal moment inequality for partial sums of strong mixing sequences and application
- Complete convergence for weighted sums of END random variables and its application to nonparametric regression models
- Complete convergence for arrays of rowwise negatively superadditive-dependent random variables and its applications
- On the Central Limit Theorem for $\varphi$-Mixing Arrays of Random Variables
- On Strong Mixing Conditions for Stationary Gaussian Processes
- On Complete Convergence for Nonstationary ϕ-Mixing Random Variables
- Complete consistency for the estimator of nonparametric regression models based on extended negatively dependent errors
- Asymptotic normality for the estimator of non parametric regression model under ϕ-mixing errors
- Some Limit Theorems for Stationary Processes
- Fixed-design regression for linear time series
- Fixed-design regression for linear time series
This page was built for publication: The asymptotic normality of the linear weighted estimator in nonparametric regression models
