基于循序-Ⅰ型删失数据的Gompertz-sinh分布的统计推断(英文)  

Statistical Inference on the Gompertz-sinh Distribution with Progressive Type-Ⅰ Censoring Scheme

作　　者：白龙[1] 程从华 

机构地区：[1]宁夏师范学院数学与计算机科学学院,宁夏固原756000 [2]岭南师范学院数学与计算机科学学院,广东湛江524048

出　　处：《应用数学》2016年第1期104-116,共13页Mathematica Applicata

基　　金：Supported by the National Natural Science Foundation of China(71171103);the Distinguished Young Talents in Higher Education of Guangdong(2012LYM 0089)

摘　　要：本文研究在循序-I型删失数据情形下Gompertz-sinh分布的统计推断问题.利用处理删失数据的EM算法,讨论Gompertz-sinh分布未知参数的最大似然估计(MLE)问题.为了讨论未知参数的近似置信区间估计,基于遗失信息原则,给出观测Fisher信息矩阵.为了演示本文的方法,给出相关数值模拟结果和一个真实数据实例.In this article, the statistical inference problems on the Gompertz-sinh distribution with a progressive type-I censoring scheme are studied.The EM algorithm is applied to deal with the incomplete data case for computing MLEs. Using a missing information principle, the observed Fisher information matrix is obtained for constructing the asymptotic confidence interval of parameters. The method is discussed via some simulation studies and an example is provided for demonstrative purposes.

关 键 词：最大似然估计 EM算法 循序型删失 Fisher信息矩阵 

分 类 号：O212.1[理学—概率论与数理统计] O213.2[理学—数学]