The multivariate Bayesian structural time series (MBSTS) model as a generalized version of many structural time series models, deals with inference and prediction for multiple correlated time series, where one also has the choice of using a different candidate pool of contemporaneous predictors for each target series. The MBSTS model has wide applications and is ideal for feature selection, time series forecasting, nowcasting, inferring causal impact, and others. This paper demonstrates how to use the R package mbsts for MBSTS modeling, establishing a bridge between user-friendly and developer-friendly functions in the package and the corresponding methodology. Object-oriented functions in the package are explained in the way that enables users to flexibly add or deduct some components, as well as to simplify or complicate some settings.
翻译:多种变式贝叶斯结构时间序列模型(MBSTS)是许多结构时间序列模型的通用版本,涉及多个相关时间序列的推论和预测,在多个相关时间序列中,人们也可以选择对每个目标序列使用不同的候选同期预测器库。 MBSTS模型具有广泛的应用,对于特征选择、时间序列预测、即时预报、即时预报、推断因果影响等都是理想的。本文展示了如何使用R包 mbsts进行MBSTS建模,在包件中的用户友好和开发者友好功能与相应方法之间建立桥梁。对包件中面向目标的功能的解释方式是,使用户能够灵活地添加或扣减某些部件,以及简化某些设置或使之复杂化。