Journal•ISSN: 2090-8431
Journal of Statistics Applications & Probability
Natural Sciences Publishing
About: Journal of Statistics Applications & Probability is an academic journal published by Natural Sciences Publishing. The journal publishes majorly in the area(s): Statistics & Estimator. It has an ISSN identifier of 2090-8431. Over the lifetime, 470 publications have been published receiving 1933 citations. The journal is also known as: JSAP.
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TL;DR: In this article, a generalization of the log-logistic distribution, called the transmuted log logistic distribution (TMLD), is proposed and studied, and the estimation of the model parameters is performed by maximum likelihood method.
Abstract: A generalization of the log-logistic distribution so-called the transmuted log-logistic distribution is proposed and studied. Various structural properties including explicit expressions for the moments, quantiles, mean deviations of the new distribution are derived. The estimation of the model parameters is performed by maximum likelihood method. We hope that the new distribution proposed here will serve as an alternative model to the other models which are available in the literature for modeling positive real data in many areas.
88 citations
TL;DR: In this article, the authors generalize the generalized Rayleigh distribution using the quadratic rank transmutation map studied by Shaw et al. (9) to develop a transmuted generalized rayleigh distribution, and provide a comprehensive description of the mathematical properties of the subject distribution along with its reliability.
Abstract: In this article, we generalize the generalized Rayleigh distribution using the qu adratic rank transmutation map studied by Shaw et al. (9) to develop a transmuted generalized Rayleigh distribution. We provide a comprehensive description of the mathematical properties of the subject distribution along with its reliability behav ior. The usefulness of the transmuted generalized Rayleigh distribution for modeling data is illustrated using real data.
64 citations
63 citations
45 citations
TL;DR: In this article, a multicomponent system of k components having strengths following k independent and identically distruted random variables and each component experiencing a random stress Y is considered.
Abstract: A multicomponent system of k components having strengths following k– independently and identically distr ibuted random variables and each component experiencing a random stress Y is considered. The system is regarded as alive only if at least sout ofk (s< k) strengths exceed the stress. The reliability of such a system is obtained whe n strength, stress variates are given by inverse Rayleigh distribution with different scale parameters. The reliability is estimated using th e Moment method and ML method of estimation when samples drawn from strength and stress distributions. The reliability e stimators are compared asymptotically. The small sample comparison of the reliability estimates is made through Monte Carlo simulation.
37 citations