5 citations · 5 across the 8 of their papers we have counts for
3 papers · 1 filter
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…