5 citations · 13 across the 8 of their papers we have counts for
8 papers
Function on Scalar Regression with Complex Survey Designs
Lily Koffman, Sunan Gao, Xinkai Zhou +3
Large health surveys increasingly collect high-dimensional functional data from wearable devices, and function on scalar regression (FoSR) is used to quantify the relationship betw…
Prediction Inference Using Generalized Functional Mixed Effects Models
Xinkai Zhou, Erjia Cui, Joseph Sartini +1
We introduce inferential methods for prediction based on functional random effects in generalized functional mixed effects models. This is similar to the inference for random effec…
Fast Bayesian Functional Principal Components Analysis
Joseph Sartini, Xinkai Zhou, Liz Selvin +2
Functional Principal Components Analysis (FPCA) is a widely used analytic tool for dimension reduction of functional data. Traditional implementations of FPCA estimate the principa…
Generalized Conditional Functional Principal Component Analysis
Yu Lu, Xinkai Zhou, Erjia Cui +4
We propose generalized conditional functional principal components analysis (GC-FPCA) for the joint modeling of the fixed and random effects of non-Gaussian functional outcomes. Th…
An AI-Driven Multimodal Smart Home Platform for Continuous Monitoring and Assistance in Post-Stroke Motor Impairment
Chenyu Tang, Ruizhi Zhang, Shuo Gao +21
At-home rehabilitation for post-stroke patients presents significant challenges, as continuous, personalized care is often limited outside clinical settings. Moreover, the lack of…
Generalized Multilevel Functional Principal Component Analysis with Application to NHANES Active Inactive Patterns
Xinkai Zhou, Julia Wrobel, Ciprian M. Crainiceanu +1
Between 2011 and 2014 NHANES collected objectively measured physical activity data using wrist-worn accelerometers for tens of thousands of individuals for up to seven days. In thi…
Proximal MCMC for Bayesian Inference of Constrained and Regularized Estimation
Xinkai Zhou, Qiang Heng, Eric C. Chi +1
This paper advocates proximal Markov Chain Monte Carlo (ProxMCMC) as a flexible and general Bayesian inference framework for constrained or regularized estimation. Originally intro…
Star discrepancy for new stratified random sampling I: optimal expected star discrepancy
Jun Xian, Xiaoda Xu, Xinkai Zhou
We introduce a class of convex equivolume partitions. Expected star discrepancy results are compared for stratified samples under these partitions, including simple random samples.…