Identification of Shared Components in Large Ensembles of Time Series Using Dimension Reduction
利用降维识别大规模时间序列集合中的共享成分
In this article we present a framework for parsimonious modeling of large ensembles of time series. The idea is to identify a small number of stochastic time series components such that each series in the ensemble is a weighted sum of series-specific realizations of the components. We present an estimation procedure that is computationally tractable for large datasets. Through simulations, we argue that the estimators perform well. We illustrate the method using two…