289 citations · 554 across the 25 of their papers we have counts for
12 papers · 1 filter
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…
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…
Fast Generalized Functional Principal Components Analysis
Andrew Leroux, Ciprian Crainiceanu, Julia Wrobel
We propose a new fast generalized functional principal components analysis (fast-GFPCA) algorithm for dimension reduction of non-Gaussian functional data. The method consists of: (…
Simple fixed-effects inference for complex functional models
So Young Park, Ana-Maria Staicu, Luo Xiao +1
We propose simple inferential approaches for the fixed effects in complex functional mixed effects models. We estimate the fixed effects under the independence of functional residu…
Fast Covariance Estimation for Sparse Functional Data
Luo Xiao, Cai Li, William Checkley +1
Smoothing of noisy sample covariances is an important component in functional data analysis. We propose a novel covariance smoothing method based on penalized splines and associate…
High-dimensional Multivariate Mediation: with Application to Neuroimaging Data
Oliver Y. Chén, Ciprian M. Crainiceanu, Elizabeth L. Ogburn +3
Mediation analysis has become an important tool in the behavioral sciences for investigating the role of intermediate variables that lie in the path between a randomized treatment…
Improving Reliability of Subject-Level Resting-State fMRI Parcellation with Shrinkage Estimators
Amanda F. Mejia, Mary Beth Nebel, Haochang Shou +5
A recent interest in resting state functional magnetic resonance imaging (rsfMRI) lies in subdividing the human brain into anatomically and functionally distinct regions of interes…
Fast Covariance Estimation for High-dimensional Functional Data
Luo Xiao, David Ruppert, Vadim Zipunnikov +1
For smoothing covariance functions, we propose two fast algorithms that scale linearly with the number of observations per function. Most available methods and software cannot smoo…