Smoothing splines on Riemannian manifolds, with applications to 3D shape space
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DOI: 10.1111/rssb.12402
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References listed on IDEAS
- Alfred Kume & Ian L. Dryden & Huiling Le, 2007. "Shape-space smoothing splines for planar landmark data," Biometrika, Biometrika Trust, vol. 94(3), pages 513-528.
- Lizhen Lin & Brian St. Thomas & Hongtu Zhu & David B. Dunson, 2017. "Extrinsic Local Regression on Manifold-Valued Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1261-1273, July.
- Emil Cornea & Hongtu Zhu & Peter Kim & Joseph G. Ibrahim, 2017. "Regression models on Riemannian symmetric spaces," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(2), pages 463-482, March.
- Zhu, Hongtu & Chen, Yasheng & Ibrahim, Joseph G. & Li, Yimei & Hall, Colin & Lin, Weili, 2009. "Intrinsic Regression Models for Positive-Definite Matrices With Applications to Diffusion Tensor Imaging," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 1203-1212.
- Peter E. Jupp & John T. Kent, 1987. "Fitting Smooth Paths to Spherical Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 36(1), pages 34-46, March.
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Cited by:
- Valerio Varano & Stefano Gabriele & Franco Milicchio & Stefan Shlager & Ian Dryden & Paolo Piras, 2022. "Geodesics in the TPS Space," Mathematics, MDPI, vol. 10(9), pages 1-20, May.
- García-Morales, Vladimir, 2021. "A constructive theory of shape," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
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