Bayes model averaging of cyclical decompositions in economic time series
经济时间序列周期分解的贝叶斯模型平均
Abstract A flexible decomposition of a time series into stochastic cycles under possible non‐stationarity is specified, providing both a useful data analysis tool and a very wide model class. A Bayes procedure using Markov Chain Monte Carlo (MCMC) is introduced with a model averaging approach which explicitly deals with the uncertainty on the appropriate number of cycles. The convergence of the MCMC method is substantially accelerated through a convenient reparametrization…