التفاصيل البيبلوغرافية
| العنوان: |
Composite Quantile Regression for Varying Coefficient Models with Response Data Missing at Random |
| المؤلفون: |
Shuanghua Luo, Cheng-yi Zhang, Meihua Wang |
| المصدر: |
Symmetry; Volume 11; Issue 9; Pages: 1065 |
| بيانات النشر: |
Multidisciplinary Digital Publishing Institute |
| سنة النشر: |
2019 |
| المجموعة: |
MDPI Open Access Publishing |
| مصطلحات موضوعية: |
varying coefficient model, composite quantile regression, missing at random, inverse probability weighting, imputed method |
| الوصف: |
Composite quantile regression (CQR) estimation and inference are studied for varying coefficient models with response data missing at random. Three estimators including the weighted local linear CQR (WLLCQR) estimator, the nonparametric WLLCQR (NWLLCQR) estimator, and the imputed WLLCQR (IWLLCQR) estimator are proposed for unknown coefficient functions. Under some mild conditions, the proposed estimators are asymptotic normal. Simulation studies demonstrate that the unknown coefficient estimators with IWLLCQR are superior to the other two with WLLCQR and NWLLCQR. Moreover, bootstrap test procedures based on the IWLLCQR fittings is developed to test whether the coefficient functions are actually varying. Finally, a type of investigated real-life data is analyzed to illustrated the applications of the proposed method. |
| نوع الوثيقة: |
text |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| العلاقة: |
https://dx.doi.org/10.3390/sym11091065Test |
| DOI: |
10.3390/sym11091065 |
| الإتاحة: |
https://doi.org/10.3390/sym11091065Test |
| حقوق: |
https://creativecommons.org/licenses/by/4.0Test/ |
| رقم الانضمام: |
edsbas.CD448A60 |
| قاعدة البيانات: |
BASE |
