A BERRY-ESSEEN TYPE BOUND OF REGRESSION ESTIMATOR BASED ON LINEAR PROCESS ERRORS
From MaRDI portal
Publication:3602143
DOI10.4134/JKMS.2008.45.6.1753zbMath1154.62032MaRDI QIDQ3602143
Publication date: 12 February 2009
Published in: Journal of the Korean Mathematical Society (Search for Journal in Brave)
Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Inference from stochastic processes (62M99)
Related Items (14)
The Berry-Esseen bounds of wavelet estimator for regression model whose errors form a linear process with a \(\rho\)-mixing ⋮ Adaptive edge weighting for graph-based learning algorithms ⋮ A Berry-Esseen bound of wavelet estimation for a nonparametric regression model under linear process errors based on LNQD sequence ⋮ Asymptotic normality of a wavelet estimator for asymptotically negatively associated errors ⋮ The Berry–Esseen-type bound for the G-M estimator in a nonparametric regression model with α-mixing errors ⋮ Asymptotic properties of wavelet estimators in semiparametric regression models under dependent errors ⋮ Berry-Esseen bounds for wavelet estimator in a regression model with linear process errors ⋮ Berry-Esseen bounds of weighted kernel estimator for a nonparametric regression model based on linear process errors under a LNQD sequence ⋮ The Berry-Esseen bound of a wavelet estimator in non-randomly designed nonparametric regression model based on ANA errors ⋮ Multi-parametric solution-path algorithm for instance-weighted support vector machines ⋮ Multi-output learning via spectral filtering ⋮ The Berry-Esseen type bounds of the weighted estimator in a nonparametric model with linear process errors ⋮ Asymptotic properties of wavelet estimators in heteroscedastic semiparametric model based on negatively associated innovations ⋮ A Berry-Esseen Type Bound of Wavelet Estimator Under Linear Process Errors Based on a Strong Mixing Sequence
This page was built for publication: A BERRY-ESSEEN TYPE BOUND OF REGRESSION ESTIMATOR BASED ON LINEAR PROCESS ERRORS