Institute of Statistical Studies & Research, Department of Mathematical Statistics, Cairo University, Egypt.
Faculty of Commerce, Department of Statistics, South Valley University, Egypt.
J Adv Res. 2015 Nov;6(6):895-905. doi: 10.1016/j.jare.2014.08.005. Epub 2014 Aug 24.
A new generalization of the Lindley distribution is recently proposed by Ghitany et al. [1], called as the power Lindley distribution. Another generalization of the Lindley distribution was introduced by Nadarajah et al. [2], named as the generalized Lindley distribution. This paper proposes a more generalization of the Lindley distribution which generalizes the two. We refer to this new generalization as the exponentiated power Lindley distribution. The new distribution is important since it contains as special sub-models some widely well-known distributions in addition to the above two models, such as the Lindley distribution among many others. It also provides more flexibility to analyze complex real data sets. We study some statistical properties for the new distribution. We discuss maximum likelihood estimation of the distribution parameters. Least square estimation is used to evaluate the parameters. Three algorithms are proposed for generating random data from the proposed distribution. An application of the model to a real data set is analyzed using the new distribution, which shows that the exponentiated power Lindley distribution can be used quite effectively in analyzing real lifetime data.
Ghitany 等人最近提出了林德利分布的一个新推广,称为幂林德利分布。Nadarajah 等人引入了林德利分布的另一种推广,称为广义林德利分布。本文提出了林德利分布的更广泛推广,将这两种推广都包含在内。我们将这个新的推广称为指数幂林德利分布。新分布非常重要,因为它包含了一些广泛知名的分布作为特殊子模型,除了上述两种模型外,还有林德利分布等。它还为分析复杂的真实数据集提供了更多的灵活性。我们研究了新分布的一些统计性质。我们讨论了分布参数的最大似然估计。最小二乘法用于评估参数。提出了三种从建议分布生成随机数据的算法。利用新分布对实际数据集进行了分析,结果表明指数幂林德利分布可以有效地用于分析实际寿命数据。