Bayesian semiparametric inference on long-range dependence
长程相依的贝叶斯半参数推断
We develop a Bayesian semiparametric procedure for the analysis of stationary long‐range dependent time series. We use frequency domain methods to partition the infinite‐dimensional parameter space into regions where genuine prior information on the form of the spectral density is available, and others where vague prior beliefs are adopted; the solution to the partition problem, which is equivalent to bandwidth choice from a frequentist point of view, is obtained via Bayes…