Weighted empirical likelihood for heteroscedastic varying coefficient partially non‐linear models with missing data-Reference-Cited by-同舟云学术

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Weighted empirical likelihood for heteroscedastic varying coefficient partially non‐linear models with missing data

Published:2021-05-21 Issue:1 Volume:10 Page:
ISSN:2049-1573
Container-title:Stat
language:en
Short-container-title:Stat

Author:

Fan Guo‐Liang¹^ORCID,Wang Lu‐Lu¹,Xu Hong‐Xia²³

Affiliation:

1. School of Economics and Management Shanghai Maritime University Shanghai 201306 China

2. School of data sciences Zhejiang University of Finance and Economics Zhejiang 310018 China

3. Department of Mathematics Shanghai Maritime University Shanghai 201306 China

Funder

Natural Science Foundation of Shanghai

National Natural Science Foundation of China

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/sta4.353

Reference29 articles.

1. Nonlinear Regression Analysis and Its Applications

2. Adjusted Empirical Likelihood and its Properties

3. Penalized empirical likelihood for high-dimensional partially linear varying coefficient model with measurement errors

4. Empirical likelihood for heteroscedastic partially linear errors-in-variables model with α-mixing errors

5. Profile likelihood inferences on semiparametric varying-coefficient partially linear models

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Additive distortion measurement errors regression models with exponential calibration;Journal of Statistical Computation and Simulation;2022-04-30

2. Statistical Inference for the Heteroscedastic Partially Linear Varying-Coefficient Errors-in-Variables Model with Missing Censoring Indicators;Discrete Dynamics in Nature and Society;2021-06-07

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