1403/01/10
اکبر اصغر زاده

اکبر اصغر زاده

مرتبه علمی: استاد
ارکید:
تحصیلات: دکترای تخصصی
اسکاپوس:
دانشکده: دانشکده علوم ریاضی
نشانی:
تلفن: 011-54302476

مشخصات پژوهش

عنوان
Confidence sets for the two-parameter Rayleigh distribution under progressive censoring
نوع پژوهش
JournalPaper
کلیدواژه‌ها
Constrained optimization, Confidence regions, Lagrange method , Nonlinear programming, Progressively censored data
سال
2017
مجله APPLIED MATHEMATICAL MODELLING
شناسه DOI
پژوهشگران Akbar Asgharzadeh ، Arturo Fernadez ، Mosa Abdi

چکیده

Exact confidence intervals and regions are proposed for the location and scale parameters of the Rayleigh distribution. These sets are valid for complete data, and also for standard and progressive failure censoring. Constrained optimization problems are solved to find the minimum-size confidence sets for the Rayleigh parameters with the required confidence level. The smallest-area confidence region is derived by simultaneously solving four nonlinear equations. Three numerical examples regarding remission times of leukemia patients, strength data and the titanium content in an aircraft-grade alloy, as well as a simulation study, are included for illustrative purposes. Further applications in hypothesis testing and the construction of pointwise and simultaneous confidence bands are also pointed out.