论文标题
在一个统一普遍的马歇尔 - olkin和泊松G家族的家庭中
On a family that unifies Generalized Marshall-Olkin and Poisson-G family of distribution
论文作者
论文摘要
提出了一个新的分配家庭，统一了广义的Marshall-Olkin（GMO）和Poisson-G（P-G）。密度和存活函数表示为P-G家族的无限混合物。得出了分位数函数，渐近分子，形状，随机排序，力矩生成函数，顺序统计，概率加权矩和rényi熵。提出了具有较大样本特性的最大似然估计。蒙特卡洛模拟用于检查偏差的模式和最大似然估计器的均方误差。与家族的某些重要子模型进行建模时的比较的说明揭示了拟议家庭的实用性。
Unifying the generalized Marshall-Olkin (GMO) and Poisson-G (P-G) a new family of distribution is proposed. Density and the survival function are expressed as infinite mixtures of P-G family. The quantile function, asymptotes, shapes, stochastic ordering, moment generating function, order statistics, probability weighted moments and Rényi entropy are derived. Maximum likelihood estimation with large sample properties is presented. A Monte Carlo simulation is used to examine the pattern of the bias and the mean square error of the maximum likelihood estimators. An illustration of comparison with some of the important sub models of the family in modeling a real data reveals the utility of the proposed family.
