首页 | 本学科首页   官方微博 | 高级检索  
     


Estimation and test procedures for composite quantile regression with covariates missing at random
Affiliation:1. CEREMADE, Université Paris-Dauphine, Place du Maréchal de Lattre de Tassigny, 75775, Paris, France;2. Université Paris-Est, LAMA (UMR 8050), UPEMLV, UPEC, CNRS, F-77454, Marne-la-Vallée, France;1. Department of Statistics and Operations Research, College of Sciences, Kuwait University, Kuwait;2. Department of Statistics, College of Science, Shiraz University, Iran;3. Faculty of Mathematics and Computer Science, Amirkabir University, Iran;1. Nanyang Business School, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore;2. Department of Economics, York University, 4700 Keele Street, Toronto, Ontario M3J 1P3, Canada;1. Department of Genitourinary Oncology, Moffitt Cancer Center, Tampa, FL;2. Department of Biostatistics, Moffitt Cancer Center, Tampa, FL;1. Institut Claudius-Regaud, 20-24, rue du Pont-Saint-Pierre, 31052 Toulouse, France;2. Centre Oscar-Lambret, Unité de méthodologie et biostatistique, 3, rue Frédéric-Combemale, BP 307, 59020 Lille cedex, France;3. Institut Gustave-Roussy, Medical Oncology Department, 94800 Villejuif, France;4. Centre François-Baclesse, 14076 Caen, France;5. Centre Georges-François-Leclerc, 21000 Dijon, France;6. Grand Hôpital de Charleroi, 3 Grand Rue, Charleroi, Belgium;7. R&D Unicancer, 101, rue de Tolbiac, 75654 Paris, France
Abstract:In this paper, we study the weighted composite quantile regression (WCQR) for general linear model with missing covariates. We propose the WCQR estimation and bootstrap test procedures for unknown parameters. Simulation studies and a real data analysis are conducted to examine the finite performance of our proposed methods.
Keywords:Composite quantile regression  General linear model  Missing covariates  Bootstrap
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号