کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7377453 | 1480116 | 2016 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Robust and efficient estimation with weighted composite quantile regression
ترجمه فارسی عنوان
برآورد پایدار و کارآمد با رگرسیون کیفی وزن کامپوزیت
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موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
فیزیک ریاضی
چکیده انگلیسی
In this paper we introduce a weighted composite quantile regression (CQR) estimation approach and study its application in nonlinear models such as exponential models and ARCH-type models. The weighted CQR is augmented by using a data-driven weighting scheme. With the error distribution unspecified, the proposed estimators share robustness from quantile regression and achieve nearly the same efficiency as the oracle maximum likelihood estimator (MLE) for a variety of error distributions including the normal, mixed-normal, Student's t, Cauchy distributions, etc. We also suggest an algorithm for the fast implementation of the proposed methodology. Simulations are carried out to compare the performance of different estimators, and the proposed approach is used to analyze the daily S&P 500 Composite index, which verifies the effectiveness and efficiency of our theoretical results.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physica A: Statistical Mechanics and its Applications - Volume 457, 1 September 2016, Pages 413-423
Journal: Physica A: Statistical Mechanics and its Applications - Volume 457, 1 September 2016, Pages 413-423
نویسندگان
Xuejun Jiang, Jingzhi Li, Tian Xia, Wanfeng Yan,