方差分析中的贝叶斯估计问题研究  

Bayesian Estimation Study in Variance Analysis Model

作　　者：孙舒曼[1] 腾德雄 胡锡健[1] 

机构地区：[1]新疆大学数学与系统科学学院,新疆乌鲁木齐

出　　处：《统计学与应用》2017年第5期508-515,共8页Statistical and Application

摘　　要：贝叶斯估计是一种简单的参数估计方法,是通过已经知道的数据来估计未知参数的先验分布的方法,这使得贝叶斯估计能充分的利用先验信息得到更合理的估计结果。本文先介绍贝叶斯估计方法的背景和思路,再用贝叶斯估计方法得到方差分析模型中参数估计的具体表达式,通过编程进行数值模拟求解,并进行实例分析。Bayesian estimation is a simple parameter estimation method through the already known data to estimate the unknown parameters of the prior distribution method, which makes the bayesian estimation can make full use of prior information to get a more reasonable estimate results. This paper first introduces the background of the bayesian estimation method and train of thought, and then uses bayesian estimation method to get the concrete expression of the parameter estimation in the analysis of variance model, numerical simulations by programming to solve. At the same time, applying bayesian estimation method is analyzed in the analysis of variance model.

关 键 词：方差分析模型 贝叶斯估计 无信息先验分布 后验分布 

分 类 号：F2[经济管理—国民经济]