Network regression and its inference
Dr Can Le is an Assistant Professor in the Department of Statistics at the University of California, Davis. He received his PhD in statistics from the University of Michigan, Ann Arbor. His main research interest is statistical network analysis.
Network data, representing interactions and relationships between units, have become ubiquitous with the rapid development of science and technology. Analyzing such complex and structurally novel data requires new ideas and tools beyond the scope of classical statistics. In this talk, we will assume that a standard response-predictors data set is available, and observations are connected by a network. We will introduce a new framework for estimating and making inference of regression coefficients with network effects. Inference requirements in the presence of observational errors related to the network structure will also be discussed. Time: 10.00 am – 11.30 am (Vietnam time, GMT+7), Friday, Nov 13, 2020 This is an online seminar and will be streaming on our Youtube VinAI Research.
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