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Title: Factor modeling of multivariate time series: A frequency components approach Authors:  Raanju Sundararajan - Southern Methodist University (United States) [presenting]
Abstract: A frequency-domain factor model method for multivariate second-order stationary time series is proposed. The aim is to find contemporaneous linear transforms of the observed multivariate series that leads to a lower-dimensional factor series that is allowed to be multivariate stationary. Frequency components of the observed series are assumed to be linearly generated by the corresponding frequency components of a latent factor series using frequency-specific factor loading matrices. These loading matrices are then estimated using an eigendecomposition of symmetric non-negative definite matrices involving the real and imaginary parts of the spectral matrix. The factor dimension is estimated using nonparametric bootstrap tests. Consistency results concerning the estimation of eigenvalues, eigenvectors and the loading matrices are provided. The numerical performance of the proposed method is illustrated through simulation examples and an application to modeling resting-state fMRI data from autistic individuals is demonstrated.