摘要
基于充分统计量建立帕累托分布在完全样本下参数的一种新联合置信域.通过置信域的平均面积,定义参数的估计效率,并通过蒙特卡洛模拟与经典置信域进行比较,结果显示新的置信域比经典置信域更精确.最后,实例分析验证了所获得的结果.
Based on a sufficient statistic,we propose a new joint confidence region for parameters of Pareto distribution under complete samples.By the average area of confidence region,efficiency of estimation is defined. Compared with classical confidence regions by Monte Carlo simulation and a numerical example,the newly proposed confidence region is shown to be more accurate in most cases.
作者
周俊梅
ZHOU Junmei(College of Mathematics and Statistics,Hainan Normal Univeisity,Haikou 571158,China;College of Mathematics and Statistics,Yunnan University,Kunming 650091,China)
出处
《昆明理工大学学报（自然科学版）》
CAS
北大核心
2018年第6期131-138,共8页
Journal of Kunming University of Science and Technology(Natural Science)
基金
National Natural Science Foundation of China(11361022
11861030)
Young Teachers Development Program at College of Mathematics and Statistics,Hainan Normal University(hnkfj201804)
关键词
帕累托分布
置信域
估计效率
模拟
Pareto distribution
confidence region
estimation efficiency
simulation
