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Smoothing splines on Riemannian manifolds, with applications to 3D shape space

  • Published:2020-12-02 Issue:1 Volume:83 Page:108-132
  • ISSN:1369-7412
  • Container-title:Journal of the Royal Statistical Society: Series B (Statistical Methodology)
  • language:en
  • Short-container-title:J R Stat Soc Series B

Author:

Kim Kwang‐Rae1,Dryden Ian L.2,Le Huiling2,Severn Katie E.2

Affiliation:

1. SAS Korea Seoul Korea

2. University of Nottingham Nottingham UK

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Reference39 articles.

1. Elementary Differential Geometry

2. Bojanowski M.(2017)lspline: Linear Splines with Convenient Parametrisations. R package version 1.0‐0.

3. Regression models on Riemannian symmetric spaces

4. Dryden I.L.(2019)Shapes: Statistical Shape Analysis. R package version 1.2.5.

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1. Probabilistic Principal Curves on Riemannian Manifolds;IEEE Transactions on Pattern Analysis and Machine Intelligence;2024-07

2. GLS‐PIA: n‐Dimensional Spherical B‐Spline Curve Fitting based on Geodesic Least Square with Adaptive Knot Placement;Computer Graphics Forum;2024-04-24

3. Interpretable discriminant analysis for functional data supported on random nonlinear domains with an application to Alzheimer’s disease;Journal of the Royal Statistical Society Series B: Statistical Methodology;2024-03-22

4. Bézier Splines Interpolation on Stiefel and Grassmann Manifolds;Journal of Computational Mathematics;2023-11

5. Smoothing Splines for Discontinuous Signals;Journal of Computational and Graphical Statistics;2023-09-27
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