کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1149834 | 957898 | 2008 | 17 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A pre-test like estimator dominating the least-squares method
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موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
ریاضیات کاربردی
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چکیده انگلیسی
We develop a pre-test type estimator of a deterministic parameter vector β in a linear Gaussian regression model. In contrast to conventional pre-test strategies, that do not dominate the least-squares (LS) method in terms of mean-squared error (MSE), our technique is shown to dominate LS when the effective dimension is greater than or equal to 4. Our estimator is based on a simple and intuitive approach in which we first determine the linear minimum MSE (MMSE) estimate that minimizes the MSE. Since the unknown vector β is deterministic, the MSE, and consequently the MMSE solution, will depend in general on β and therefore cannot be implemented. Instead, we propose applying the linear MMSE strategy with the LS substituted for the true value of β to obtain a new estimate. We then use the current estimate in conjunction with the linear MMSE solution to generate another estimate and continue iterating until convergence. As we show, the limit is a pre-test type method which is zero when the norm of the data is small, and is otherwise a non-linear shrinkage of LS.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Statistical Planning and Inference - Volume 138, Issue 10, 1 October 2008, Pages 3069-3085
Journal: Journal of Statistical Planning and Inference - Volume 138, Issue 10, 1 October 2008, Pages 3069-3085
نویسندگان
Yonina C. Eldar, Jacob Slava Chernoi,