Wavelet Thresholds for Matrix-Variate Normal Distribution Under The Reflected Normal Loss
محل انتشار: پنجمین کنفرانس بین المللی محاسبات نرم
سال انتشار: 1402
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 18
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شناسه ملی سند علمی:
CSCG05_083
تاریخ نمایه سازی: 9 اردیبهشت 1403
چکیده مقاله:
The matrix-variate normal distribution is a probability distribution that is a generalization of the multivariate normal distribution to matrix-valued random variables. In this paper, we introduce a wavelet shrinkage estimator based on Stein’s unbiased risk estimate (SURE) threshold for matrix-variate normal distribution. We find a new SURE threshold for soft thresholding wavelet shrinkage estimator under the reflected normal loss function in low dimensional cases. Also, we obtain the restricted wavelet shrinkage estimator based on non-negative sub matrix of the mean matrix. Finally, we present a simulation study to test the validity of the wavelet shrinkage.
کلیدواژه ها:
Matrix ، variate normal distribution ، Shrinkage estimtion ، SURE threshold ، Wavelet shrinkage ، Reflected normal loss function
نویسندگان
Hamid Karamikabir
Faculty of Intelligent Systems Engineering and Data Science, department of Statistics, Persian Gulf UniversityBushehr
Fatemeh Jamhiri
Faculty of Intelligent Systems Engineering and Data Science, department of Statistics, Persian Gulf University,Bushehr
Mahmoud Afshari
Faculty of Intelligent Systems Engineering and Data Science, department of Statistics, Persian Gulf University,Bushehr