23,030 research outputs found
A Three Parameter Generalized Lindley Distribution: Properties and Application
In this paper, we introduced a new class of lifetime distribution and considered the mathematical properties of one of the sub models called a three parameter generalized Lindley distribution (TPGLD). The new class of distributions generalizes some of the Lindley family of distribution such as the power Lindley distribution, the Sushila distribution, the Lindley-Pareto distribution, the Lindley-half logistic distribution and the classical Lindley distribution. An application of the TPGLD to two real lifetime data sets reveals its superiority over the exponentiated power Lindley distribution, the exponentiated Lindley geometric distribution, the power Lindley distribution, the Lindley-exponential distribution and the classical one parameter Lindley distribution in modeling the lifetime data sets under study
POISSON TRANSMUTED LINDLEY DISTRIBUTION
The main purpose of this paper is to introduce a new discrete compound distribution, namely Poisson Transmuted Lindley distribution (PTL) which offers a more flexible model for analyzing some types of countable data. The proposed distribution is accommodate unimodel, bathtub as well as decreasing failure rates. Most of the statistical and reliability measures are derived. For the estimation purposes the method of moment and maximum likelihood methods are studied for PTL. Simulation studies are conducted to investigate the performance of the maximum likelihood estimators. A real life application for PTL is introduced to test its goodness of fit and examine its performance compared with some other distributions
Transmuted Lindley-Geometric Distribution and its applications
A functional composition of the cumulative distribution function of one
probability distribution with the inverse cumulative distribution function of
another is called the transmutation map. In this article, we will use the
quadratic rank transmutation map (QRTM) in order to generate a flexible family
of probability distributions taking Lindley geometric distribution as the base
value distribution by introducing a new parameter that would offer more
distributional flexibility. It will be shown that the analytical results are
applicable to model real world data.Comment: 20 pages, 6 figures. arXiv admin note: substantial text overlap with
arXiv:1309.326
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