Posterior Mode Estimation by Extended Kalman Filtering for Multivariate Dynamic Generalized Linear Models
用扩展卡尔曼滤波估计多变量动态广义线性模型的后验众数
A family of multivariate dynamic generalized linear models is introduced as a general framework for the analysis of time series with observations from the exponential family. Besides common conditionally Gaussian models, this article deals with univariate models for counted and binary data and, as the most interesting multivariate case, models for nonstationary multicategorical time series. For univariate responses, a related yet different class of models has been introduced…