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20182020
most citedModeling Symmetric Positive Definite Matrices with An Application to Functional Brain Connectivity

1 citations · 2 across the 3 of their papers we have counts for

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5 papers · 1 filter

stat.ME2020

Multivariate functional responses low rank regression with an application to brain imaging data

Xiucai Ding, Dengdeng Yu, Zhengwu Zhang +1

We propose a multivariate functional responses low rank regression model with possible high dimensional functional responses and scalar covariates. By expanding the slope functions…

stat.ME20191 cited

Modeling Symmetric Positive Definite Matrices with An Application to Functional Brain Connectivity

Zhenhua Lin, Dehan Kong, Qiang Sun

In neuroscience, functional brain connectivity describes the connectivity between brain regions that share functional properties. Neuroscientists often characterize it by a time se…

stat.ME2019

Identifiability of causal effects with multiple causes and a binary outcome

Dehan Kong, Shu Yang, Linbo Wang

Unobserved confounding presents a major threat to causal inference from observational studies. Recently, several authors suggest that this problem may be overcome in a shared confo…

stat.ME2019

Nonparametric Matrix Response Regression with Application to Brain Imaging Data Analysis

Wei Hu, Tianyu Pan, Dehan Kong +1

With the rapid growth of neuroimaging technologies, a great effort has been dedicated recently to investigate the dynamic changes in brain activity. Examples include time course ca…

stat.ME2018

Matrix Linear Discriminant Analysis

Wei Hu, Weining Shen, Hua Zhou +1

We propose a novel linear discriminant analysis approach for the classification of high-dimensional matrix-valued data that commonly arises from imaging studies. Motivated by the e…