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Title: Some extensions to covariance regression Authors:  Tao Zou - The Australian National University (Australia) [presenting]
Abstract: Recently, a novel covariance regression model is proposed to study the relationship between the covariance matrix of responses and their associated similarity matrices induced by auxiliary information. To broaden the usefulness of the covariance regression model, the normality assumption is relaxed and effective and efficient methodology is developed in order to obtain inferences for covariance regression models. Moreover, sophisticated statistics are developed for some extensions of covariance regression. Both the theory and practice of statistics, and substantive fields of applications with covariance matrices of data involved, such as geostatistics, sociology and economics will be influenced.