4 citations · 6 across the 9 of their papers we have counts for
9 papers
Minimax prediction in the Functional Autoregressive Model
André Mas, Angelina Roche
The Functional Autoregressive Model (FAR) generalizes the multivariate AR(1) model in Time Series Analysis to functional data. It serves as a historical foundational point in the s…
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…
PCA for Point Processes
Franck Picard, Vincent Rivoirard, Angelina Roche +1
We introduce a novel statistical framework for the analysis of replicated point processes that allows for the study of point pattern variability at a population level. By treating…
Minimax estimation of Functional Principal Components from noisy discretized functional data
Ryad Belhakem, Franck Picard, Vincent Rivoirard +1
Functional Principal Component Analysis is a reference method for dimension reduction of curve data. Its theoretical properties are now well understood in the simplified case where…
Adaptive nonparametric estimation of a component density in a two-class mixture model
Gaelle Chagny, Antoine Channarond, Van Ha Hoang +1
A two-class mixture model, where the density of one of the components is known, is considered. We address the issue of the nonparametric adaptive estimation of the unknown probabil…
Lasso in infinite dimension: application to variable selection in functional multivariate linear regression
Angelina Roche
It is more and more frequently the case in applications that the data we observe come from one or more random variables taking values in an infinite dimensional space, e.g. curves.…