Optimal variance estimation without estimating the mean function

DOI10.3150/12-BEJ432zbMath1281.62105arXiv1312.3046MaRDI QIDQ2435225

Yanyuan Ma, Yuedong Wang, Tie Jun Tong

Publication date: 4 February 2014

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1312.3046

zbMATH Keywords

asymptotic normalitynonparametric regressiongeneralized least squaresdifference-based estimatoroptimal boundsresidual variance

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)

Related Items (15)

Bayesian jackknife empirical likelihood for the error variance in linear regression models ⋮ Optimal difference-based estimation for partially linear models ⋮ Asymptotically optimal differenced estimators of error variance in nonparametric regression ⋮ Optimal variance estimation based on lagged second-order difference in nonparametric regression ⋮ Efficient error variance estimation in non‐parametric regression ⋮ Equivariant variance estimation for multiple change-point model ⋮ Variance estimation in nonparametric regression with jump discontinuities ⋮ On variance estimation under shifts in the mean ⋮ Testing discontinuities in nonparametric regression ⋮ Difference-based variance estimation in nonparametric regression with repeated measurement data ⋮ On the choice of difference sequence in a unified framework for variance estimation in nonparametric regression ⋮ Autocovariance Estimation in Regression with a Discontinuous Signal and m‐Dependent Errors: A Difference‐Based Approach ⋮ A least squares method for variance estimation in heteroscedastic nonparametric regression ⋮ Jackknife empirical likelihood for the error variance in linear models ⋮ Robust scale estimation under shifts in the mean

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