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stat.ME2022
Spline Estimation of Functional Principal Components via Manifold Conjugate Gradient Algorithm
Shiyuan He, Hanxuan Ye, Kejun He
Functional principal component analysis has become the most important dimension reduction technique in functional data analysis. Based on B-spline approximation, functional princip…
stat.ME2022
Functional Bayesian Networks for Discovering Causality from Multivariate Functional Data
Fangting Zhou, Kejun He, Kunbo Wang +2
Multivariate functional data arise in a wide range of applications. One fundamental task is to understand the causal relationships among these functional objects of interest, which…
stat.ME2022★ 5 cited
Causal Discovery with Heterogeneous Observational Data
Fangting Zhou, Kejun He, Yang Ni
We consider the problem of causal discovery (structure learning) from heterogeneous observational data. Most existing methods assume a homogeneous sampling scheme, which leads to m…