Poisson - Gompertz分布及其性质与应用

A. Chaudhary, L. Sapkota, Vijay Kumar
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引用次数: 1

摘要

本文以泊松生成族为基础,以Gompertz分布为基准,生成了泊松- Gompertz (PGZ)分布。给出了PGZ分布的一些特征。对于所提出的模型的参数估计,最大似然估计(MLE)与Cramer-Von-Mises估计(CVME)和最小二乘估计(LSE)方法一起应用。我们基于极大似然估计构造了渐近置信区间。采用R软件平台进行计算。结合实际生活数据集说明了该模型的应用,并通过不同的检验统计量和图解方法考察了所观察模型的拟合优度。我们发现,与考虑的其他模型相比,引入的分布提供了更好的数据集拟合,具有更大的灵活性
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Poisson Gompertz Distribution with Properties and Applications
Here, a new distribution using the Poisson generating family with Gompertz distribution as baseline distribution have been generated called Poisson Gompertz (PGZ) distribution. Some distributional features of the PGZ distribution are presented. For the parameter estimates of the presented model, Maximum likelihood Estimation (MLE) is applied along with Cramer-Von-Mises estimation (CVME) and least-square estimation (LSE) methods. We have constructed the asymptotic confidence intervals based on maximum likelihood estimates. R software platform was used to perform the computations. The application of the proposed model has been illustrated by considering the data set obtained from real life and investigated the goodness of fit attained by the observed model via different test statistics and graphical methods. We have found that the distribution that is introduced provides better fit to the dataset taken with more flexibility as compared to other models in consideration
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