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محمود افشاري

محمود افشاری

مرتبه علمی: دانشیار
نشانی: دانشکده مهندسی سیستم های هوشمند و علوم داده - گروه آمار
تحصیلات: دکترای تخصصی / آمار
تلفن: 07731223328
دانشکده: دانشکده مهندسی سیستم های هوشمند و علوم داده

مشخصات پژوهش

عنوان Two new Bayesian-wavelet thresholds estimations of elliptical distribution parameters under non-linear exponential balanced loss
نوع پژوهش مقالات در نشریات
کلیدواژه‌ها
Admissible estimator; Generalized Bayes estimator; Minimax estimator; Non-linear exponential balanced-loss function; Shrinkage estimator; Stein’s unbiased risk estimator; Wavelet estimator
مجله COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
شناسه DOI https://doi.org/10.1080/03610918.2023.2245173
پژوهشگران زیبا بتوندی (نفر اول) ، محمود افشاری (نفر دوم) ، حمید کرمی کبیر (نفر سوم)

چکیده

The estimation of mean vector parameters is very important in elliptical and spherically models. Among different methods, the Bayesian and shrinkage estimation are interesting. In this paper, the estimation of p-dimensional location parameter for p-variate elliptical and spherical distributions under an asymmetric loss function is investigated. We find generalized Bayes estimator of location parameters for elliptical and spherical distributions. Also we show the minimaxity and admissibility of generalized Bayes estimator in class of spherical distribution: We introduce two new shrinkage soft wavelet threshold estimators based on Huang shrinkage wavelet estimator (empirical) and Stein’s unbiased risk estimator (SURE) for elliptical and spherical distributions under non-linear exponential-balanced loss function. At the end, we present a simulation study to test the validity of the class of proposed estimators and physicochemical properties of the tertiary structure data set that is given to test the efficiency of this estimators in denoising.