Asymptotic efficiency of ridge estimator in linear and semiparametric linear models

DOI10.1016/J.SPL.2011.08.019zbMath1229.62093OpenAlexW2030088142MaRDI QIDQ654469

June Luo

Publication date: 28 December 2011

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2011.08.019

zbMATH Keywords

continuityhigh dimensiondifferencing sequence

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Asymptotic properties of nonparametric inference (62G20)

Related Items (1)

Using thresholding difference-based estimators for variable selection in partial linear models

Cites Work

• Profile-kernel likelihood inference with diverging number of parameters
• Semiparametric estimation of censored selection models with a nonparametric selection mechanism
• An elementary estimator of the partial linear model
• Estimation in a semiparametric partially linear errors-in-variables model
• A difference based approach to the semiparametric partial linear model
• The discovery of mean square error consistency of a ridge estimator
• Variable screening in predicting clinical outcome with high-dimensional microarrays
• Goodness-of-Fit Tests for Parametric Regression Models
• Ridge Regression: Biased Estimation for Nonorthogonal Problems

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