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Coefficient of Variation of Topp-Leone Distribution Under Adaptive Type-II Progressive Censoring Scheme: Bayesian and Non-Bayesian Approach

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The coefficient of variation (CV) of a population is defined as the ratio of the population standard deviation to the population mean. In applied statistics, the CV is widely used. However, inference concerning the coefficient of variation of non-normal distributions are rarely reported. So in this paper, Bayesian and non-Bayesian approach is adopted to estimate coefficient of variation (CV) of Topp-Leone distribution (TLD) under an adaptive Type-II Progressive Censoring Scheme. This approach will give us a point estimate as well as the empirical sampling distribution of CV. The results in the cases of progressive Type II censoring, Type II censoring and complete sample are special cases. The results of maximum likelihood and parametric bootstrap techniques are also proposed. Numerical example is presented for illustrative purposes. Results from simulation studies assessing the performance of our proposed method are included.

Keywords: Adaptive Type-II Progressive Censoring Scheme; Bayesian Estimation; Bootstrap Confidence Interval; Coefficient of Variation; Maximum Likelihood Estimatiom; Topp-Leone

Document Type: Research Article

Affiliations: 1: Department of Mathematics, Faculty of Science, Taif University, Kingdom of Saudi Arabia 2: Department of Mathematics, Faculty of Science, Fayoum University, Egypt 3: College of Science and Computer Engineering, Taibah University, Yanbu, KSA

Publication date: 01 November 2015

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  • Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
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