Mlinex损失函数下逆伽马分布尺度参数的Bayes估计

Bayesian Estimation for Scale Parameter of Inverse Gamma Distribution under Mlinex Loss Function

在Mlinex损失函数下,本文首次讨论了逆伽马分布尺度参数的Bayes估计及其可容许性,并对该分布的一个充分统计量的逆线性形式的容许性进行了分析,然后使用蒙特卡洛模拟阐明小样本情形下尺度参数的Bayes估计的精度一般优于其最大似然估计和Minimax估计,与一致最小方差无偏估计相当。

Under Mlinex loss function,Bayesian estimation and its admissibility for the scale parameter of inverse gamma distribution are discussed for the first time,and the admissibility of the inverse linear form of a sufficient statistics is also analyzed.Then,Monte Carlo simulation is used to clarify the better performance of Bayes estimate than the maximum likelihood and the minimax estimates,which is as good as the uniformly minimum variance unbiased estimate from estimated error for small samples.