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Wavelet threshold based on Stein's unbiased risk estimators of restricted location parameter in multivariate normal

التفاصيل البيبلوغرافية
العنوان: Wavelet threshold based on Stein's unbiased risk estimators of restricted location parameter in multivariate normal
المؤلفون: Mahmoud Afshari, Fazlollah Lak, Hamid Karamikabir
المصدر: J Appl Stat
بيانات النشر: Informa UK Limited, 2020.
سنة النشر: 2020
مصطلحات موضوعية: Statistics and Probability, Shrinkage estimator, 021103 operations research, Location parameter, 0211 other engineering and technologies, Estimator, Multivariate normal distribution, Articles, 02 engineering and technology, 01 natural sciences, 010104 statistics & probability, Wavelet, Statistics, Mean vector, 0101 mathematics, Statistics, Probability and Uncertainty, Value (mathematics), Mathematics
الوصف: In this paper, the problem of estimating the mean vector under non-negative constraints on location vector of the multivariate normal distribution is investigated. The value of the wavelet threshold based on Stein's unbiased risk estimators is calculated for the shrinkage estimator in restricted parameter space. We suppose that covariance matrix is unknown and we find the dominant class of shrinkage estimators under Balance loss function. The performance evaluation of the proposed class of estimators is checked through a simulation study by using risk and average mean square error values.
تدمد: 1360-0532
0266-4763
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e0e5c6ae98983f1529fc4d020f4830ba
https://doi.org/10.1080/02664763.2020.1772209
حقوق: OPEN
رقم الأكسشن: edsair.doi.dedup.....e0e5c6ae98983f1529fc4d020f4830ba
قاعدة البيانات: OpenAIRE
الوصف
تدمد:13600532
02664763