空间滞后模型的贝叶斯估计

本文采用Bayes方法对空间滞后模型进行全面分析。在构建模型的贝叶斯框架时，对模型系数与误差方差分别选取正态先验分布和逆伽玛先验分布，这样以便获得参数的联合后验分布和条件后验分布。在抽样估计时，文章主要使用MCMC方法，同时还设计了一个简单随机游动Metropolis抽样器，以方便从空间权重因子系数的条件后验分布中进行抽样。最后应用所建议的方法进行数值模拟。

Bayesian Estimation of the Spatial Lag Model

This paper used Bayesian method to analyze the spatial lag model. When the construction of Bayesian framework, we selected normal distribution and inverse gamma distribution as prior of model coefficients and error variance in order to obtain the joint posterior distribution and the conditional posterior distribution of parameters. The article mainly used MCMC methods to estimate parameters, and also designed a simple random walk Metropolis sampling device, to facilitate the sampling from conditional posterior distribution of spatial weighting factor coefficient. Finally, the proposed method was used for numerical simulation.