3 citations · 6 across the 3 of their papers we have counts for
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stat.ME2008★ 2 cited
Principal components analysis for sparsely observed correlated functional data using a kernel smoothing approach
Debashis Paul, Jie Peng
In this paper, we consider the problem of estimating the covariance kernel and its eigenvalues and eigenfunctions from sparse, irregularly observed, noise corrupted and (possibly)…
stat.ME2007★ 3 cited
A geometric approach to maximum likelihood estimation of the functional principal components from sparse longitudinal data
Jie Peng, Debashis Paul
In this paper, we consider the problem of estimating the eigenvalues and eigenfunctions of the covariance kernel (i.e., the functional principal components) from sparse and irregul…