6 citations · 15 across the 13 of their papers we have counts for
6 papers · 1 filter
Causal Inference for Unobservable Multivariate Outcomes, with Applications to Brain Effective Connectivity
Haiyue Song, Ani Eloyan, Youjin Lee
Evaluating the causal effect of an intervention on multivariate outcomes is challenging when the outcomes are interdependent and derived rather than directly observed. Effective co…
Statistical Inference on Grayscale Images via the Euler-Radon Transform
Kun Meng, Mattie Ji, Jinyu Wang +4
Tools from topological data analysis have been widely used to represent binary images in many scientific applications. Methods that aim to represent grayscale images (i.e., where p…
Distributed model building and recursive integration for big spatial data modeling
Emily C. Hector, Brian J. Reich, Ani Eloyan
Motivated by the need for computationally tractable spatial methods in neuroimaging studies, we develop a distributed and integrated framework for estimation and inference of Gauss…
Randomness of Shapes and Statistical Inference on Shapes via the Smooth Euler Characteristic Transform
Kun Meng, Jinyu Wang, Lorin Crawford +1
In this article, we establish the mathematical foundations for modeling the randomness of shapes and conducting statistical inference on shapes using the smooth Euler characteristi…
Principal manifold estimation via model complexity selection
Kun Meng, Ani Eloyan
We propose a framework of principal manifolds to model high-dimensional data. This framework is based on Sobolev spaces and designed to model data of any intrinsic dimension. It in…
PCA leverage: outlier detection for high-dimensional functional magnetic resonance imaging data
Amanda F. Mejia, Mary Beth Nebel, Ani Eloyan +2
Outlier detection for high-dimensional (HD) data is a popular topic in modern statistical research. However, one source of HD data that has received relatively little attention is…