Gamma分布的区间数据参数估计的迭代算法  

An Iterative Algorithm of Estimating Parameters in Gamma Distribution with Interval Data

作　　者：胡思艺 HU Siyi(SchoolofStatistics,EastChinaNormalUniversity,Shanghai,200062,China)

机构地区：[1]华东师范大学统计学院,上海200062

出　　处：《应用概率统计》2022年第4期505-520,共16页Chinese Journal of Applied Probability and Statistics

摘　　要：本文研究Gamma分布在分类数据、Ⅰ型区间删失数据、Ⅱ型区间删失数据三种情况下的一种基于极大似然估计和用无梯度信息谱剩余法改进的EM算法的参数估计迭代方法,并证明算法的强相合性.模拟结果显示本文提出的迭代方法在保证精确度的同时可以极大缩短运行时间,估计的均方误差会随样本量增大而趋于零.This paper studies an iterative method of estimating paramneters in Gamma distribution based on maximum likelihood estimation and EM algorithm improved by non gradient information spectrum residual method in the case of lassified data,Type-I interval censered data,Type-II interval censered data,and it proves:the strong consistency of the algorithm.The simulation results show that the iterative method proposed in this paper can greatly shorten the running time while ensuring the accuracy,the estimated mean square error tends to zero with the increase of sample size.

关 键 词：GAMMA分布 区间数据 极大似然估计 EM算法 无梯度信息谱剩余法 

分 类 号：O212.1[理学—概率论与数理统计]