Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (2)
  • Open Access

    ARTICLE

    Modeling Reliability Engineering Data Using Scale-Invariant Quasi-Inverse Lindley Model

    Mohamed Kayid*, Tareq Alsayed

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1847-1860, 2022, DOI:10.32604/cmc.2022.025401 - 24 February 2022

    Abstract An important property that any lifetime model should satisfy is scale invariance. In this paper, a new scale-invariant quasi-inverse Lindley (QIL) model is presented and studied. Its basic properties, including moments, quantiles, skewness, kurtosis, and Lorenz curve, have been investigated. In addition, the well-known dynamic reliability measures, such as failure rate (FR), reversed failure rate (RFR), mean residual life (MRL), mean inactivity time (MIT), quantile residual life (QRL), and quantile inactivity time (QIT) are discussed. The FR function considers the decreasing or upside-down bathtub-shaped, and the MRL and median residual lifetime may have a bathtub-shaped… More >

  • Open Access

    ARTICLE

    Generalized Marshall Olkin Inverse Lindley Distribution with Applications

    Rashad Bantan1, Amal S. Hassan2, Mahmoud Elsehetry3, *

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1505-1526, 2020, DOI:10.32604/cmc.2020.010887 - 30 June 2020

    Abstract In this article, a new generalization of the inverse Lindley distribution is introduced based on Marshall-Olkin family of distributions. We call the new distribution, the generalized Marshall-Olkin inverse Lindley distribution which offers more flexibility for modeling lifetime data. The new distribution includes the inverse Lindley and the Marshall-Olkin inverse Lindley as special distributions. Essential properties of the generalized Marshall-Olkin inverse Lindley distribution are discussed and investigated including, quantile function, ordinary moments, incomplete moments, moments of residual and stochastic ordering. Maximum likelihood method of estimation is considered under complete, Type-I censoring and Type-II censoring. Maximum likelihood More >

Displaying 1-10 on page 1 of 2. Per Page