289 citations · 554 across the 25 of their papers we have counts for
28 papers
Tutorial for Bayesian Factor Models
Peter Dunson, Ciprian M. Crainiceanu
Bayesian Factor Models (BFM) are well-established models that decompose the observed variability in a set of mean-zero, independent, and uncorrelated factors (random effects). Whil…
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…
Inference for the Extended Functional Cox Model: A UK Biobank Case Study
Erjia Cui, Angela Zhao, Ciprian M. Crainiceanu
Multiple studies have shown that scalar summaries of objectively measured physical activity (PA) using accelerometers are the strongest predictors of mortality, outperforming all t…
FLAME: A Model for Duration-Dependent Risk Accumulation in Episodic Temporal Exposures
Xinkai Zhou, Lee Goeddel, Nauder Faraday +1
Emerging technologies enable continuous monitoring of temporal exposures to disease risk factors, leading to complex exposure processes characterized by subject-specific numbers an…
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…