3 citations · 6 across the 3 of their papers we have counts for
3 papers
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)…
math.ST2008★ 1 cited
Consistency of restricted maximum likelihood estimators of principal components
Debashis Paul, Jie Peng
In this paper we consider two closely related problems : estimation of eigenvalues and eigenfunctions of the covariance kernel of functional data based on (possibly) irregular meas…
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…