5 citations · 5 across the 8 of their papers we have counts for
9 papers
PCA score regression: the art of losing power
Yu Lu, Nidhi Pai, Erjia Cui +1
The regression of principal component scores (RPCS) on covariates is a widely used analytic approach to detect and test for associations between functional measurements and study p…
Sufficient conditions for proper posteriors in fully-Bayesian Functional PCA
Joseph Sartini, Scott Zeger, Ciprian Crainiceanu
In a fully-Bayesian Functional Principal Components Analysis (FPCA) the principal components are treated as unknown infinite-dimensional parameters. By projecting the functional pr…
Functional Moments Regression
Mingyuan Li, Martin A. Lindquist, Edward Gunning +1
The Gaussian Process (GP) assumption is often used in functional data analysis. We propose a method to assess departures from the GP assumption, both in terms of the shape of the d…
Bayesian Multivariate Sparse Functional Principal Components Analysis
Joseph Sartini, Scott Zeger, Ciprian Crainiceanu
Functional Principal Components Analysis (FPCA) provides a parsimonious, semi-parametric model for multivariate, sparsely-observed functional data. Frequentist FPCA approaches esti…
Walking Fingerprinting Using Wrist Accelerometry During Activities of Daily Living in NHANES
Lily Koffman, John Muschelli, Ciprian Crainiceanu
We propose a method for identifying individuals based on their continuously monitored wrist-worn accelerometry during activities of daily living. The method consists of three steps…
Tutorial on Bayesian Functional Regression Using Stan
Ziren Jiang, Ciprian Crainiceanu, Erjia Cui
This manuscript provides step-by-step instructions for implementing Bayesian functional regression models using Stan. Extensive simulations indicate that the inferential performanc…
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…
Comparing Step Counting Algorithms for High-Resolution Wrist Accelerometry Data in NHANES 2011-2014
Lily Koffman, Ciprian Crainiceanu, John Muschelli
Purpose: To quantify the relative performance of step counting algorithms in studies that collect free-living high-resolution wrist accelerometry data and to highlight the implicat…
A case study of glucose levels during sleep using fast function on scalar regression inference
Renat Sergazinov, Andrew Leroux, Erjia Cui +4
Continuous glucose monitors (CGMs) are increasingly used to measure blood glucose levels and provide information about the treatment and management of diabetes. Our motivating stud…