کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1152462 | 958288 | 2011 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A note on improving quadratic inference functions using a linear shrinkage approach
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آمار و احتمال
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: A note on improving quadratic inference functions using a linear shrinkage approach A note on improving quadratic inference functions using a linear shrinkage approach](/preview/png/1152462.png)
چکیده انگلیسی
In some commonly used longitudinal clinical trials designs, the quadratic inference functions (QIF) method fails to work due to non-invertible estimation of the optimal weighting matrix. We propose a modified QIF method, in which the optimal weighting matrix is estimated by a linear shrinkage estimator, replacing the sample covariance matrix. We prove that the linear shrinkage estimator is consistent and asymptotically optimal under the expected quadratic loss, and will have more stable numerical performance than the sample covariance matrix. Simulations show that numerical improvements are acquired in light of a higher percentage of convergence, and smaller standard errors and mean square errors of parameter estimates.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Statistics & Probability Letters - Volume 81, Issue 3, March 2011, Pages 438–445
Journal: Statistics & Probability Letters - Volume 81, Issue 3, March 2011, Pages 438–445
نویسندگان
Peisong Han, Peter X.-K. Song,