摘要
主要在数据缺失的情况下研究了伽马分布的参数估计与假设检验,位置参数已知的条件下,给出形状参数的极大似然估计,并证明了形状参数估计的强相合性与渐进正态性,并对两总体参数之差的置信区间和假设检验做出分析,最后做随机模拟验证了其合理性.
Parameter estimation and hypothesis test are studied on gamma distribution under missing data samples, the position of known parameters, the maximum likelihood given shape parameter estimation,and proves that the shape parameter estimation the strong consistency and asymptotic normality, and the two overall parameter difference of confidence intervals and hypothesis testing analysis.finally, the rationality Of the model is verified by simulation.
出处
《数学的实践与认识》
北大核心
2017年第13期196-201,共6页
Mathematics in Practice and Theory
关键词
伽马分布
缺失数据
极大似然估计
假设检验
Gamma distribution
missing dat~
maximum likelihood estimation
hypothesis testing.
