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stat.ME2026
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…
stat.ME2026
Block Empirical Likelihood Inference for Longitudinal Generalized Partially Linear Single-Index Models
Tianni Zhang, Yuyao Wang, Yu Lu +1
Generalized partially linear single-index models (GPLSIMs) provide a flexible and interpretable semiparametric framework for longitudinal outcomes by combining a low-dimensional pa…
stat.ME2024
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…