摘要
对常见的混合模型进行了推广,提出了异分布混合模型的概念.以二项分布和泊松分布为例,详细给出了异分布混合模型的数学定义,以及异分布混合模型参数的贝叶斯估计.在参数估计中,选择狄尼克莱分布、贝塔分布和伽玛分布作为相关参数的共轭先验分布,利用MCMC算法对模型的参数进行了后验模拟,用后验均值作为参数的估计值.最后将参数的估计结果与模型的真实值进行比较,证明了估计结果的可靠性.
We generalize the common hybrid models and put forward the concept of heterogeneous mixed models. Taking the binomial and Poisson distributions as an example, the mathematical definitions of the heterogeneous mixed models are given in detail. In the parameter estimation, we choose the Dignley distribu- tion, the beta distribution and the gamma distribution as the conjugate prior distribution of the relevant pa- rameters, and use the MCMC algorithm to carry on the posteriori simulation of the model parameters, using the posterior mean value as the parameter Finally, the result of parameter estimation is compared with the re- al value of the model, which proves the reliability of the estimation result.
作者
张波
刘鹤飞
王坤
Zhang Bo;Liu Hefei;Wang Kun(Party Committee Graduate Work Department,Yunnan University,Kunming Yunnan 650504,China;School of Mathematics and Statistics,Qujing Normal University,Qujing Yunnan 655011,China)
出处
《曲靖师范学院学报》
2018年第6期1-4,共4页
Journal of Qujing Normal University
基金
曲靖师范学院校级青年项目"隐马尔科夫多维分布的参数估计"(2018QN004)
关键词
异分布混合
贝叶斯估计
先验分布
MCMC算法
Different distribution Mixed model
Bayesian estimation
Prior distribution
MCMC algorithm
