Bayesian Vector Autoregressions with Stochastic Volatility
提出一种贝叶斯方法处理带随机波动率的向量自回归模型，其中精度矩阵的乘性演化由多元贝塔变量驱动，并给出了精确更新公式，自回归参数估计则采用重要性抽样方法。
This paper proposes a Bayesian approach t o a v ector autoregression with stochastic volatility, where the multiplicative e v olution of the precision matrix is driven by a m ultivariate beta variate.Exact updating formulas are given to the nonlinear ltering of the precision matrix.Estimation of the autoregressive parameters requires numerical methods: an importance-sampling based approach is explained here.i