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Omid Naghshineh Arjmand

Publications and source records attributed to Omid Naghshineh Arjmand.

2 recordsLinked to original sources
arXiv2025

A Recursive Exponential-Gamma Mixture: a New Generalized of the Lindley Distribution

The Lindley distribution was first introduced by Lindley in 1958 for Bayesian computations. Over the past years, various generalizations of this distribution have been proposed by different authors. The generalized Lindley distributions sometimes have many parameters, and although they show good flexibility, their statistical form becomes complicated. In this article, we propose a new and simple distribution determined by the recursive relation of the Lindley distribution and the Gamma distribution with specific weights. Subsequently, some statistical properties of this distribution are examined, and with real numerical examples, its superiority over the Lindley generalizations is demonstrated.

math.ST↗
arXiv2025

Reliability Analysis of a 1-out-of-n Cold Standby Redundant System under the Generalized Lindley Distribution

Cold standby 1-out-of-n redundant systems are well-established models in system reliability engineering. To date, reliability analyses of such systems have predominantly assumed exponential, Erlang, or Weibull failure distributions for their components. The Lindley distribution and its generalizations represent a significant class of statistical distributions in reliability engineering. Certain generalized Lindley distributions, due to the appealing characteristics of their hazard functions, can serve as suitable alternatives to other well-known lifetime distributions like the Weibull. This study investigates the reliability of a 1-out-of-n cold standby redundant system with perfect and imperfect switching, assuming that the active component failure times follow the Generalized Lindley distribution. We derive a closed-form expression for the system reliability. To achieve this, the distribution of the sum of n independent and identically distributed random variables following the Generalized Lindley distribution is first determined using the moment-generating function approach.

stat.AP↗