دورية أكاديمية
Two-step variable selection in quantile regression models
| العنوان: | Two-step variable selection in quantile regression models |
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| المؤلفون: | FAN Yali |
| المصدر: | Journal of Shanghai Normal University (Natural Sciences), Vol 44, Iss 3, Pp 270-283 (2015) |
| بيانات النشر: | Academic Journals Center of Shanghai Normal University |
| سنة النشر: | 2015 |
| المجموعة: | Directory of Open Access Journals: DOAJ Articles |
| مصطلحات موضوعية: | LASSO, adaptive LASSO, quantile regression, high dimensional, Science (General), Q1-390 |
| الوصف: | We propose a two-step variable selection procedure for high dimensional quantile regressions, in which the dimension of the covariates, p n is much larger than the sample size n . In the first step, we perform ℓ 1 penalty, and we demonstrate that the first step penalized estimator with the LASSO penalty can reduce the model from an ultra-high dimensional to a model whose size has the same order as that of the true model, and the selected model can cover the true model. The second step excludes the remained irrelevant covariates by applying the adaptive LASSO penalty to the reduced model obtained from the first step. Under some regularity conditions, we show that our procedure enjoys the model selection consistency. We conduct a simulation study and a real data analysis to evaluate the finite sample performance of the proposed approach. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English Chinese |
| تدمد: | 1000-5137 |
| العلاقة: | http://qktg.shnu.edu.cn/zrb/shsfqkszrb/ch/reader/create_pdf.aspx?file_no=201503005&flag=1&year_id=2015&quarter_id=3Test; https://doaj.org/toc/1000-5137Test; https://doaj.org/article/0b3a9265da564afa92cf841a56e3726fTest |
| DOI: | 10.3969/J.ISSN.100-5137.2015.03.005 |
| الإتاحة: | https://doi.org/10.3969/J.ISSN.100-5137.2015.03.005Test https://doaj.org/article/0b3a9265da564afa92cf841a56e3726fTest |
| رقم الانضمام: | edsbas.FED1DF36 |
| قاعدة البيانات: | BASE |
| تدمد: | 10005137 |
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| DOI: | 10.3969/J.ISSN.100-5137.2015.03.005 |