论文标题
Kronecker图形模型的自回旋识别
Autoregressive Identification of Kronecker Graphical Models
论文作者
论文摘要
我们解决了该问题，以估计与自回归高斯随机过程相对应的Kronecker图形模型。后者由功率频谱密度函数完全描述，其逆逆向支持kronecker乘积分解。我们提出了一种贝叶斯方法来估计这种模型。我们通过一些数值实验来测试提出方法的有效性。我们还将程序应用于城市污染监测数据。
We address the problem to estimate a Kronecker graphical model corresponding to an autoregressive Gaussian stochastic process. The latter is completely described by the power spectral density function whose inverse has support which admits a Kronecker product decomposition. We propose a Bayesian approach to estimate such a model. We test the effectiveness of the proposed method by some numerical experiments. We also apply the procedure to urban pollution monitoring data.
