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Principal components analysis for sparsely observed correlated
  functional data using a kernel smoothing approach

Principal components analysis for sparsely observed correlated functional data using a kernel smoothing approach

7 July 2008
D. Paul
Jie Peng
ArXiv (abs)PDFHTML

Papers citing "Principal components analysis for sparsely observed correlated functional data using a kernel smoothing approach"

3 / 3 papers shown
Testing Separability of Functional Time Series
Testing Separability of Functional Time Series
P. Constantinou
P. Kokoszka
M. Reimherr
149
8
0
16 Jan 2018
Functional Data Analysis by Matrix Completion
Functional Data Analysis by Matrix Completion
Marie-Hélène Descary
V. Panaretos
252
33
0
03 Sep 2016
A geometric approach to maximum likelihood estimation of the functional
  principal components from sparse longitudinal data
A geometric approach to maximum likelihood estimation of the functional principal components from sparse longitudinal data
Jie Peng
D. Paul
523
128
0
29 Oct 2007
1
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