Two-step variable selection in quantile regression models
We propose a two-step variable selection procedure for high dimensional quantile regressions, in which the dimension of the covariates,<i> p<sub>n</sub></i> is much larger than the sample size <i>n</i>. In the first step, we perform <i>ℓ</i><sub>...
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| Format: | Article |
| Language: | English |
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Academic Journals Center of Shanghai Normal University
2015-06-01
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| Series: | Journal of Shanghai Normal University (Natural Sciences) |
| Subjects: | |
| Online Access: | http://qktg.shnu.edu.cn/zrb/shsfqkszrb/ch/reader/create_pdf.aspx?file_no=201503005&flag=1&year_id=2015&quarter_id=3 |