A Bayesian Non-Stationary Heteroskedastic Time Series Model for Multivariate Critical Care Data
用于多变量重症监护数据的贝叶斯非平稳异方差时间序列模型
We propose a multivariate GARCH model for non-stationary health time series by modifying the variance of the observations of the standard state space model. The proposed model provides an intuitive way of dealing with heteroskedastic data using the conditional nature of state space models. We follow the Bayesian paradigm to perform the inference procedure. In particular, we use Markov chain Monte Carlo methods to obtain samples from the resultant posterior distribution. Due…