样本数据缺失情形下泊松过程的强度估计和检验  

Estimation and Test for Two Poisson Processes with Missing Data

作　　者：孟俊才[1] 贺瑞缠[1] 

机构地区：[1]西北大学,西安710127

出　　处：《价值工程》2011年第32期297-298,共2页Value Engineering

基　　金：西北大学211基金资助

摘　　要：文章讨论了样本数据缺失情形下泊松过程的强度估计和检验问题。用极大似然估计、矩估计法和最小二乘估计法对强度进行估计,分别得出了极大似然估计强度的迭代方法,矩估计值及最小二乘估计值。证明了矩估计值和最小二乘估计值的无偏性和相合性,导出了其统计量的极限分布。最后,对两个Poisson过程的差异进行了假设检验同时给出渐近置信区间。This paper estimates and inspects strength of the poisson process under the condition of the missing data. By the moment,maximum likelihood and least-square methods, the parameter is estimated. And iteration method of maximum likelihood estimation, moment and least-square estimated value are obtained. Then unbiased sex and consistency of estimated value of moment and least-square are proved. Limited distribution of statistics is got. Finally, the difference of two poisson processes is tested and confidence interval is given.

关 键 词：缺失数据:极大似然估计 矩估计 最小二乘估计 极限分布 假设检验 

分 类 号：O212[理学—概率论与数理统计]