Nonparametric regression with correlated errors.
type: Item
instance of: scholarly article
title: Nonparametric regression with correlated errors.
zbMATH Open document ID: 1059.62537
author: Yuedong Wang
author: Yuhong Yang
author: Jean D. Opsomer
published in: Statistical Science
publication date: 2004-05-27T00:00:00Z
Mathematics Subject Classification ID: 62G08
Mathematics Subject Classification ID: 65T60
zbMATH DE Number: 2068925
zbMATH Keywords: Kernel regression
zbMATH Keywords: splines
zbMATH Keywords: wavelet regression
zbMATH Keywords: adaptive estimation
zbMATH Keywords: smoothing parameter selection
describes a project that uses: gss
describes a project that uses: longmemo
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1214/ss/1009213287
OpenAlex ID: W2090373435
cites work: On large-sample estimation for the mean of a stationary random sequence
cites work: Theory & Methods: Krige, Smooth, Both or Neither?
cites work: Theory of Reproducing Kernels
cites work: Q4865042
cites work: Uniform Consistency of Kernel Estimators of a Regression Function Under Generalized Conditions
cites work: Q3327527
cites work: Bandwidth selection for kernel estimate with correlated noise
cites work: Comparison of two bandwidth selectors with dependent errors
cites work: Strong uniform convergence rates in robust nonparametric time series analysis and prediction: Kernel regression estimation from dependent observations
cites work: ON SPLINE SMOOTHING WITH AUTOCORRELATED ERRORS
cites work: Minimax estimation via wavelet shrinkage
cites work: How to overcome the curse of long-memory errors
cites work: Q4272803
cites work: Nonparametric regression with long-range dependence
cites work: On bandwidth choice in nonparametric regression with both short- and long-range dependent errors
cites work: How Far Are Automatically Chosen Regression Smoothing Parameters From Their Optimum?
cites work: Regression Smoothing Parameters That Are Not Far From Their Optimum
cites work: Nonparametric smoothing and lack-of-fit tests
cites work: Q4272612
cites work: Q4298924
cites work: Extension of the Gauss-Markov theorem to include the estimation of random effects
cites work: Choice of bandwidth for kernel regression when residuals are correlated
cites work: Q4363939
cites work: Some results on Tchebycheffian spline functions and stochastic processes
cites work: The Performance of Cross-Validation and Maximum Likelihood Estimators of Spline Smoothing Parameters
cites work: Nonparametric spline regression with autoregressive moving average errors
cites work: Contrasts under long-range correlations
cites work: Q4892528
cites work: Rates of convergence of estimates, Kolmogorov's entropy and the dimensionality reduction principle in regression
cites work: Q4381615
cites work: Fitting a bivariate additive model by local polynomial regression
cites work: A Fully Automated Bandwidth Selection Method for Fitting Additive Models
cites work: Q5679553
cites work: An Effective Bandwidth Selector for Local Least Squares Regression
cites work: Multivariate locally weighted least squares regression
cites work: The use of polynomial splines and their tensor products in multivariate function estimation. (With discussion)
cites work: Polynomial splines and their tensor products in extended linear modeling. (With discussions)
cites work: Q4194315
cites work: Q3324909
cites work: A comparison of GCV and GML for choosing the smoothing parameter in the generalized spline smoothing problem
cites work: Q3996207
cites work: Behavior near zero of the distribution of GCV smoothing parameter estimates
cites work: Smoothing spline ANOVA for exponential families, with application to the Wisconsin epidemiological study of diabetic retinopathy. (The 1994 Neyman Memorial Lecture)
cites work: Function estimation via wavelet shrinkage for long-memory data
cites work: Nonparametric regression with dependent errors
cites work: Q4257269
cites work: Combining different procedures for adaptive regression
DOI: 10.1214/SS/1009213287
description: scientific article; zbMATH DE number 2068925