嘉宾简介 Biography

Prof. Jianhua GUO, the Vice President of Northeast Normal University, Ph.D. supervisor. He is the Convenor of Statistics Discipline Evaluation Group of the Academic Degrees Committee of the State Council, the winner of National Science Fund for Outstanding Young Scholars, and the Distinguished Professor for the Chang-Jiang Scholar Program of the Ministry of Education. In addition, Prof. GUO has been elected as the National Candidate of the New Century Millions of Talents Project, the State Council Expert for Special Allowance, IMS Fellow and ISI Elected Member. Moreover, he has been appointed as the Discipline Planning and Evaluation Group Member of National Social Science Fund, the Evaluation Expert of the National Natural Science Foundation as well as the Associate Editor of the leading statistical journal JASA and an Editorial Board Member of “Statistical Research”.

报告简介 Abstract

In this talk, I will introduce a two-way dynamic factor model (2w-DFM) for high dimensional matrix-valued time series and study some of the basic theoretical properties in terms of identifiability and estimation accuracy. The proposed model aims to capture separable and low-dimensional effects of row and column attributes and their correlations across rows, columns, and time points. Complementary to other dynamic factor models for high dimensional data, the 2w-DFM inherits the dimension reduction feature of factor models but assumes additive row and column factors for better interpretability. We provide conditions to ensure model identifiability, and consider a pseudo-likelihood-based two-step method for parameter estimation. Under an asymptotic regime where the size of the data matrices as well as the length of the time series increase, we establish that the estimators achieve the optimal rate of convergence and are asymptotically normal. The asymptotic properties are reaffirmed empirically through simulation studies.

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