摘要
结构方程模型是一种含有潜变量的经典统计学模型，被广泛应用于心理学、教育学、经济学、医学等领域。隐马尔可夫模型是一种基于随机过程的统计模型。本文将结构方程模型与隐马尔可夫模型相结合，构造了一种新的模型——隐马尔可夫结构方程模型，详细给出了隐马尔可夫结构方程模型的数学定义。为了对模型的系数进行贝叶斯估计，设定了模型参数的先验分布，然后利用MCMC方法模拟参数的后验分布，计算出了参数的后验均值作为参数的估计值。最后将参数的估计值与真值进行比较，发现估计效果良好。
The structural equation model is a classical statistical model with latent variables, which is widely used in psychology, pedagogy, economics, medicine and other fields. The hidden Markov model is a statistical model based on stochastic process. In this paper, a new model hidden Markovian structural equation model is constructed by combining the structural equation model with the hidden Markov model. The mathematical definition of the hidden Markov structure equation is given in detail. In order to estimate the coefficients of the model, the prior distribution of the model parameters is set and then the MCMC method is used to simulate the posterior distribution of the parameters. The posterior mean of the parameters is calculated as the estimated value of the parameters. Finally, the estimated value of the parameter is compared with the true value, and the estimation effect is found to be good.
出处
《数理统计与管理》
CSSCI
北大核心
2018年第2期272-279,共8页
Journal of Applied Statistics and Management
基金
云南省教育厅科研项目(2014C135Y,2015C087Y)
