Nonparametric data segmentation in multivariate time series via joint characteristic functions
利用联合特征函数对多元时间序列进行非参数分段
Summary Modern time series data often exhibit complex dependence and structural changes that are not easily characterized by shifts in the mean or model parameters. We propose a nonparametric data segmentation methodology for multivariate time series. By considering joint characteristic functions between the time series and its lagged values, our proposed method is able to detect changepoints in the marginal distribution, but also those in possibly nonlinear serial…