New Proposed Uniform-Exponential Distribution (original) (raw)
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A New Generalized Exponential Distribution: Properties and Applications
International Journal of Analysis and Applications, 2020
The exponential distribution is a popular statistical distribution to study the problems in lifetime and reliability theory. We proposed a new generalized exponential distribution, wherein exponentiated exponential and exponentiated generalized exponential distributions are sub-models of the proposed distribution. We study several important statistical and mathematical properties of the newly developed model and provide the simple expressions for the generating function, moments and mean deviations. Parameters of the proposed distribution are estimated by the technique of maximum likelihood. For two real data sets from the field of biology and engineering, the proposed distribution is compared to some existing distributions. It is found that the proposed model is more suitable and useful to study lifetime data. Thus, it gives us another alternative model for existing models.
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A new generalization of linear exponential distribution: Theory and application
The linear exponential distribution is a very well-known distribution for modeling lifetime data in reliability and medical studies. We introduce in this paper a new four-parameter generalized version of the linear exponential distribution which is called Kumaraswamy linear exponential distribution. We provide a comprehensive account of the mathematical properties of the new distributions. In particular, a closed-form expressions for the density, cumulative distribution and hazard rate function of the distribution is given. Also, the rth order moment and moment generating function are derived. The maximum likelihood estimation of the unknown parameters is discussed.
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Additive uniform exponential distribution
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The pdf of additive uniform exponential distribution is derived by using jacobean technique.Several properties like mean,variance,mgf are derived and discussed in detailed
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