A Bayesian Time Series Model of Multiple Structural Changes in Level, Trend, and Variance
水平、趋势与方差多重结构变化的贝叶斯时间序列模型
We consider a deterministically trending dynamic time series model in which multiple structural changes in level, trend, and error variance are modeled explicitly and the number, but not the timing, of the changes is known. Estimation of the model is made possible by the use of the Gibbs sampler. The determination of the number of structural breaks and the form of structural change is considered as a problem of model selection, and we compare the use of marginal likelihoods,…