| Name : R-GeodRegr
| |
| Version : 0.2.0
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp153.1.12
| Date : 2024-06-14 11:24:39
|
| Group : Development/Libraries/Other
| Source RPM : R-GeodRegr-0.2.0-lp153.1.12.src.rpm
|
| Size : 0.14 MB
| |
| Packager : (none)
| |
| Summary : Geodesic Regression
|
Description :
Provides a gradient descent algorithm to find a geodesic relationship
between real-valued independent variables and a manifold-valued
dependent variable (i.e. geodesic regression). Available manifolds are
Euclidean space, the sphere, hyperbolic space, and Kendall\'s
2-dimensional shape space. Besides the standard least-squares loss, the
least absolute deviations, Huber, and Tukey biweight loss functions can
also be used to perform robust geodesic regression. Functions to help
choose appropriate cutoff parameters to maintain high efficiency for
the Huber and Tukey biweight estimators are included, as are functions
for generating random tangent vectors from the Riemannian normal
distributions on the sphere and hyperbolic space. The n-sphere is a
n-dimensional manifold: we represent it as a sphere of radius 1 and
center 0 embedded in (n+1)-dimensional space. Using the hyperboloid
model of hyperbolic space, n-dimensional hyperbolic space is embedded
in (n+1)-dimensional Minkowski space as the upper sheet of a
hyperboloid of two sheets. Kendall\'s 2D shape space with K landmarks is
of real dimension 2K-4; preshapes are represented as complex K-vectors
with mean 0 and magnitude 1. Details are described in Shin, H.-Y. and
Oh, H.-S. (2020) < arXiv:2007.04518>. Also see Fletcher, P. T. (2013)
< doi:10.1007/s11263-012-0591-y>.
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
