26 آبان 1403
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 Extended exp-G family of distributions: Properties, applications and simulation
نوع پژوهش مقالات در نشریات
کلیدواژه‌ها
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مجله COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
شناسه DOI
پژوهشگران مراد علیزاده (نفر اول) ، محمود افشاری (نفر دوم) ، بیستون حسینی (نفر سوم) ، تیاگو رامیرز (نفر چهارم)

چکیده

In many applied areas there is a clear need for extended forms of the well-known distributions. Generally, the new distributions are flexible to model real data that present a high degree of skewness and kurtosis. Each of them is applied to solve a particular part of the classical distribution problems. In this paper, the new Extended Exp- G family of distributions is going to be introduced. In particular, G has been considered as the normal distribution and also Weibull distribution. some statistical properties such as moments, Maximum likelihood estimator and regression model have been calculated. The fitness capability of this model has been investigated by fitting this model and others based on real data sets. The maximum likelihood estimators are assessed with simulated real data from proposed model. We present the simulation in order to test validity of maximum likelihood estimators.