Weighted composite quantile regression with censoring indicators missing at random
Autor: | Jiang-Feng Wang, Wu-Xin Fu, Wei-Jun Jiang, Fang-Yin Xu |
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Rok vydání: | 2019 |
Předmět: |
Statistics and Probability
021103 operations research 0211 other engineering and technologies Linear model Asymptotic distribution Feature selection 02 engineering and technology Missing data 01 natural sciences 010104 statistics & probability Censoring (clinical trials) Statistics 0101 mathematics Composite quantile regression Mathematics |
Zdroj: | Communications in Statistics - Theory and Methods. 50:2900-2917 |
ISSN: | 1532-415X 0361-0926 |
DOI: | 10.1080/03610926.2019.1678638 |
Popis: | In this paper, we consider the weighted composite quantile regression for the linear model when the data are right censored and the censoring indicators are missing at random. The adaptive penalize... |
Databáze: | OpenAIRE |
Externí odkaz: |
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