Variable selection and semiparametric efficient estimation for the heteroscedastic partially linear single-index model-Reference-Cited by-同舟云学术

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Variable selection and semiparametric efficient estimation for the heteroscedastic partially linear single-index model

Published:2014-02 Issue: Volume:70 Page:241-256
ISSN:0167-9473
Container-title:Computational Statistics & Data Analysis
language:en
Short-container-title:Computational Statistics & Data Analysis

Author:

Lai Peng,Wang Qihua,Zhou Xiao-Hua

Funder

NIH

National Natural Science Foundation of China

Natural Science Foundation of the Jiangsu Higher Education Institutions of China

National Science Fund for Distinguished Young Scholars in China

Key Lab of Random Complex Structure and Data Science, CAS

NSF

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Statistics and Probability

Reference22 articles.

1. The Dantzig selector: statistical estimation when p is much larger than n (with discussion);Candes;Ann. Statist.,2007

2. Generalized partially linear single-index models;Carroll;J. Amer. Statist. Assoc.,1997

3. Nonparametric quasi-likelihood;Chiou;Ann. Statist.,1999

4. Uniform in bandwidth consistency of kernel-type function estimators;Einmahl;Ann. Statist.,2005

5. Local linear regression smoothers and their minimax efficiency;Fan;Ann. Statist.,1993

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2. Empirical likelihood in single-index quantile regression with high dimensional and missing observations;Journal of Statistical Planning and Inference;2023-09

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4. Model identification and selection for single-index varying-coefficient models;Annals of the Institute of Statistical Mathematics;2020-06-10

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