Model averaging for multiple quantile regression with covariates missing at random-Reference-Cited by-同舟云学术

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Model averaging for multiple quantile regression with covariates missing at random

Published:2021-02-26 Issue:11 Volume:91 Page:2249-2275
ISSN:0094-9655
Container-title:Journal of Statistical Computation and Simulation
language:en
Short-container-title:Journal of Statistical Computation and Simulation

Author:

Ding Xianwen¹,Xie Jinhan²,Yan Xiaodong³

Affiliation:

1. Department of Statistics, Jiangsu University of Technology, Changzhou, People's Republic of China

2. Key Lab of Statistical Modeling and Data Analysis of Yunnan Province, Yunnan University, Kunming, People's Republic of China

3. Zhongtai Securities Institute for Financial Studies, Shandong University, Jinan, People's Republic of China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shandong

Jiangsu Overseas Visiting Scholar Program for University Prominent Young & Middle-aged Teachers and Presidents

Major Basic Research Project of the Natural Science Foundation of the Jiangsu Higher Education Institutions

Publisher

Informa UK Limited

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Modelling and Simulation,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/00949655.2021.1890733

Reference27 articles.

1. Editorial: Model selection and efficiency-is 'Which model ...?' the right question?

2. Information Theory and Mixing Least-Squares Regressions

3. Least Squares Model Averaging

4. AVERAGING ESTIMATORS FOR REGRESSIONS WITH A POSSIBLE STRUCTURAL BREAK

5. Optimal Weight Choice for Frequentist Model Average Estimators

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1. Jackknife model averaging for linear regression models with missing responses;Journal of the Korean Statistical Society;2024-02-19

2. Model averaging for generalized linear models in diverging model spaces with effective model size;Econometric Reviews;2023-11-22

3. A two-stage prediction filling method with support vector technologies optimized competitively in stages by grey wolf optimizer and particle swarm optimization for missing fasting blood glucose;Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine;2023-10-24

4. Model averaging for generalized linear models in fragmentary data prediction;Statistical Theory and Related Fields;2022-07-30

5. A Two-Stage Prediction Filling Method with Support Vector Technologies Optimized Competitively in Stages by Grey Wolf Optimizer and Particle Swarm Optimization for Missing Fasting Blood Glucose;SSRN Electronic Journal;2022

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