Geodesic regression on spheres from a numerical optimization viewpoint

DOI10.1080/00207160.2014.884277zbMath1328.53020OpenAlexW2019690148MaRDI QIDQ3451407

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Publication date: 16 November 2015

Published in: International Journal of Computer Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207160.2014.884277

zbMATH Keywords

sequential quadratic programminggeodesicsnormal equationsconstrained nonlinear optimizationgeodesic distance

Mathematics Subject Classification ID

Numerical smoothing, curve fitting (65D10) Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Methods of local Riemannian geometry (53B21)

Related Items (2)

New computational and statistical models in science and economics ⋮ A numerical optimization approach to generate smoothing spherical splines

Uses Software

• Matlab

Cites Work

• Higher-order smoothing splines versus least squares problems on Riemannian manifolds
• The De Casteljau algorithm on Lie groups and spheres
• On the geometry of rolling and interpolation curves on \(S^n\), \(\mathrm{SO}_n\), and Grassmann manifolds
• Cubic Splines on Curved Spaces
• Morse Theory. (AM-51)
• Riemannian center of mass and mollifier smoothing
• Fitting Smooth Paths to Speherical Data
• Shape-space smoothing splines for planar landmark data
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