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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

29 October 2007
Jie Peng
D. Paul
ArXiv (abs)PDFHTML

Papers citing "A geometric approach to maximum likelihood estimation of the functional principal components from sparse longitudinal data"

5 / 5 papers shown
Title
Fast symmetric additive covariance smoothing
Fast symmetric additive covariance smoothing
Jona Cederbaum
Fabian Scheipl
S. Greven
39
16
0
22 Sep 2016
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
D. Paul
Jie Peng
135
24
0
07 Jul 2008
Consistency of restricted maximum likelihood estimators of principal
  components
Consistency of restricted maximum likelihood estimators of principal components
D. Paul
Jie Peng
125
46
0
05 May 2008
Methodology and convergence rates for functional linear regression
Methodology and convergence rates for functional linear regression
P. Hall
J. Horowitz
145
652
0
03 Aug 2007
Asymptotics for sliced average variance estimation
Asymptotics for sliced average variance estimation
Yingxing Li
Li-Xing Zhu
146
86
0
03 Aug 2007
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