摘要
对线性指数分布在平方损失下获得了参数的贝叶斯估计,并构造了相应的经验贝叶斯估计,证明了所提出的经验贝叶斯估计是渐近最优的且有收敛速度O(n-q),其中q=(s-1)(λs-1)/[s(2s+1)],1/2<λ<1-1/(2s),s≥2是一给定的整数.
Empirical Bayes estimation was derived under square loss function and empirical Bayes estimations of the parameter were constructed for linear exponential distribution. It is shown that the proposed empirical Bayes estimations are asymptotically optimal with convergence rates O (n^-q ), where, q=(s-1)(λs-1)/[s(2s+1.)], and 1/2〈λ〈1-1/(2s), s≥2 is a given integer.
出处
《华中科技大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2006年第10期122-124,共3页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(10301011)
关键词
线性指数分布
经验贝叶斯估计
收敛速度
linear exponential distribution
empirical Bayes estimation
convergence rate