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stat.ME2026
Local Fréchet Regression with Riemannian Predictors
Chang Jun Im, Jeong Min Jeon
Fréchet regression is well developed for Euclidean predictors, but local linear methods remain limited for general manifold-valued predictors. We propose local constant and local l…
stat.ME2026
Functional Principal Component Analysis for Manifold-Indexed Data
Chang Jun Im, Jeong Min Jeon
Functional principal component analysis has traditionally focused on processes indexed by Euclidean domains, although functional observations increasingly arise on curved domains.…
stat.ME2026
Local Fréchet regression with toroidal predictors
Chang Jun Im, Jeong Min Jeon
We provide the first regression framework that simultaneously accommodates responses taking values in a general metric space and predictors lying on a general torus. We propose int…