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
کلیدواژهها
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
شیوه ارجاع
Karamikabir, Hamid and Jamhiri, Fatemeh and Afshari, Mahmoud,1402,Wavelet Thresholds for Matrix-Variate Normal Distribution Under The Reflected Normal Loss,5th International Conference on Software Computing,Rudsar
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