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math.ST2026
Minimax estimation of Functional Principal Components from noisy discretized functional data: the case of smooth processes
Nassim Bourarach, Franck Picard, Vincent Rivoirard +1
We study the minimax estimation of covariance eigenfunctions and eigenvalues in functional principal component analysis when trajectories are observed at common grid points…
math.ST2026
Non-asymptotic two-sample kernel testing with the spectrally truncated normalized MMD
Perrine Lacroix, Bertrand Michel, Franck Picard +1
Kernel methods provide a flexible and powerful framework for nonparametric statistical testing by embedding probability distributions into a reproducing kernel Hilbert space (RKHS)…