289 citations · 505 across the 29 of their papers we have counts for
31 papers
Density-on-Density Regression
Yi Zhao, Abhirup Datta, Bohao Tang +2
In this study, a density-on-density regression model is introduced, where the association between densities is elucidated via a warping function. The proposed model has the advanta…
Learning sources of variability from high-dimensional observational studies
Eric W. Bridgeford, Jaewon Chung, Brian Gilbert +6
Causal inference studies whether the presence of a variable influences an observed outcome. As measured by quantities such as the "average treatment effect," this paradigm is emplo…
Longitudinal regression of covariance matrix outcomes
Yi Zhao, Brian S. Caffo, Xi Luo
In this study, a longitudinal regression model for covariance matrix outcomes is introduced. The proposal considers a multilevel generalized linear model for regressing covariance…
Regularized regression on compositional trees with application to MRI analysis
Bingkai Wang, Brian S. Caffo, Xi Luo +4
A compositional tree refers to a tree structure on a set of random variables where each random variable is a node and composition occurs at each non-leaf node of the tree. As a gen…
Identifying brain hierarchical structures associated with Alzheimer's disease using a regularized regression method with tree predictors
Yi Zhao, Bingkai Wang, Chin-Fu Liu +4
Brain segmentation at different levels is generally represented as hierarchical trees. Brain regional atrophy at specific levels was found to be marginally associated with Alzheime…
Principal Regression for High Dimensional Covariance Matrices
Yi Zhao, Brian S. Caffo, Xi Luo
This manuscript presents an approach to perform generalized linear regression with multiple high dimensional covariance matrices as the outcome. Model parameters are proposed to be…