کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1150754 | 957986 | 2006 | 18 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Empirical Bayes testing for a normal mean: variance unknown case
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
ریاضیات کاربردی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
This paper deals with the empirical Bayes testing for the mean θ of a N(θ,Ï2) distribution using a linear error loss where it is assumed that θ follows an unknown prior distribution G and variance Ï2 is fixed but unknown. An empirical Bayes test δËn is constructed. Under very mild conditions that EG[|θ|]<â and the critical point of a Bayes test is finite, δËn is shown to be asymptotically optimal, and the associated regret converges to zero at a rate O(n-1(lnn)1.5)where n is the number of past experiences available when the current component decision problem is considered. This rate achieves the optimal rate which was established by Gupta and Li (Optimal rate of convergence of monotone empirical Bayes tests for a normal mean. Technical Report 01-03, Department of Statistics, Purdue University.) for variance Ï2 known case.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Statistical Planning and Inference - Volume 136, Issue 4, 1 April 2006, Pages 1376-1393
Journal: Journal of Statistical Planning and Inference - Volume 136, Issue 4, 1 April 2006, Pages 1376-1393
نویسندگان
TaChen Liang,