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Principal Component Analysis for Functional Data on Riemannian Manifolds
  and Spheres

Principal Component Analysis for Functional Data on Riemannian Manifolds and Spheres

17 May 2017
Xiongtao Dai
Hans-Georg Müller
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Papers citing "Principal Component Analysis for Functional Data on Riemannian Manifolds and Spheres"

7 / 7 papers shown
Title
Principal Component Analysis in Space Forms
Principal Component Analysis in Space Forms
Puoya Tabaghi
Michael Khanzadeh
Yusu Wang
Sivash Mirarab
32
8
0
06 Jan 2023
Changes from Classical Statistics to Modern Statistics and Data Science
Changes from Classical Statistics to Modern Statistics and Data Science
Kai Zhang
Shan-Yu Liu
M. Xiong
39
0
0
30 Oct 2022
Exploratory Factor Analysis of Data on a Sphere
Exploratory Factor Analysis of Data on a Sphere
Fan Dai
K. Dorman
Somak Dutta
R. Maitra
14
1
0
09 Nov 2021
Additive Models for Symmetric Positive-Definite Matrices, Riemannian
  Manifolds and Lie groups
Additive Models for Symmetric Positive-Definite Matrices, Riemannian Manifolds and Lie groups
Zhenhua Lin
Hans-Georg Müller
B. Park
14
7
0
18 Sep 2020
Intrinsic Riemannian Functional Data Analysis for Sparse Longitudinal
  Observations
Intrinsic Riemannian Functional Data Analysis for Sparse Longitudinal Observations
Lingxuan Shao
Zhenhua Lin
Fang Yao
11
18
0
16 Sep 2020
Inference for spherical location under high concentration
Inference for spherical location under high concentration
D. Paindaveine
Thomas Verdebout
61
11
0
02 Jan 2019
Nonlinear manifold representations for functional data
Nonlinear manifold representations for functional data
Dong Chen
Hans-Georg Müller
83
65
0
28 May 2012
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