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 Information measures for record ranked set samples
نوع پژوهش مقالات در نشریات
کلیدواژه‌ها
Kullback-Leibler information. Record ranked set sampling design. Rényi information. Shannon entropy.
مجله Ciência e Natura
شناسه DOI https://doi.org/10.5902/2179460X19527
پژوهشگران مریم اسکندرزاده (نفر اول) ، سعید طهماسبی (نفر دوم) ، محمود افشاری (نفر سوم)

چکیده

Salehi and Ahmadi (2014) introduced a new sampling scheme for generating record-breaking data called record ranked set sampling. In this paper, we consider the uncertainty and information content of record ranked set samples (RRSS) in terms of Shannon entropy, Rényi and Kullback-Leibler (KL) information measures. We show that the difference between the Shannon entropy of RRSS and the simple random samples (SRS) is depends on the parent distribution F. We also compare the information content of RRSS with a SRS data in the uniform, exponential, Weibull, Pareto, and gamma distributions. We obtain similar results for RRSS under the Rényi information. Finally, we show that the KL information between the distribution of SRS and distribution of RRSS is distribution-free and increases as the sample size increases.