B0568
Title: Spectral inference for high dimensional time series
Authors: Danna Zhang - University of California, San Diego (United States) [presenting]
Abstract: High dimensional non-Gaussian time series data are increasingly encountered in a wide range of applications. We consider the problem of spectral inference of high dimensional time series using the framework of functional dependence measure. In particular, we establish a distributional theory on high dimensional spectra estimates by Gaussian approximation, which can be applied to address various testing problems for time series. We also develop two different resampling methods to implement spectral inference in practice and show the theoretical validity in the high dimensional setting.
