An Unobserved-Component Model With Switching Permanent and Transitory Innovations
永久与暂时创新切换的不可观测成分模型
This article proposes an unobserved-component model in which component innovations are governed by a state variable that follows a Markov process. The proposed model is capable of describing both stationary and nonstationary behaviors of real data and allows the random innovations to have permanent and transitory effects in different periods. The model also permits a deterministic trend with or without breaks and hence bridges the gap between the trend-stationary model and a…