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  • Open Access

    ARTICLE

    Entropy Bayesian Analysis for the Generalized Inverse Exponential Distribution Based on URRSS

    Amer I. Al-Omari1, Amal S. Hassan2, Heba F. Nagy2, Ayed R. A. Al-Anzi3,*, Loai Alzoubi1

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3795-3811, 2021, DOI:10.32604/cmc.2021.019061 - 24 August 2021

    Abstract This paper deals with the Bayesian estimation of Shannon entropy for the generalized inverse exponential distribution. Assuming that the observed samples are taken from the upper record ranked set sampling (URRSS) and upper record values (URV) schemes. Formulas of Bayesian estimators are derived depending on a gamma prior distribution considering the squared error, linear exponential and precautionary loss functions, in addition, we obtain Bayesian credible intervals. The random-walk Metropolis-Hastings algorithm is handled to generate Markov chain Monte Carlo samples from the posterior distribution. Then, the behavior of the estimates is examined at various record values. More >

  • Open Access

    ARTICLE

    Power Inverted Topp–Leone Distribution in Acceptance Sampling Plans

    Tahani A. Abushal1, Amal S. Hassan2, Ahmed R. El-Saeed3, Said G. Nassr4,*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 991-1011, 2021, DOI:10.32604/cmc.2021.014620 - 12 January 2021

    Abstract We introduce a new two-parameter model related to the inverted Topp–Leone distribution called the power inverted Topp–Leone (PITL) distribution. Major properties of the PITL distribution are stated; including; quantile measures, moments, moment generating function, probability weighted moments, Bonferroni and Lorenz curve, stochastic ordering, incomplete moments, residual life function, and entropy measure. Acceptance sampling plans are developed for the PITL distribution, when the life test is truncated at a pre-specified time. The truncation time is assumed to be the median lifetime of the PITL distribution with pre-specified factors. The minimum sample size necessary to ensure the… More >

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