nprotreg: Nonparametric Rotations for Sphere-Sphere Regression

Fits sphere-sphere regression models by estimating locally weighted rotations. Simulation of sphere-sphere data according to non-rigid rotation models. Provides methods for bias reduction applying iterative procedures within a Newton-Raphson learning scheme. Cross-validation is exploited to select smoothing parameters. See Marco Di Marzio, Agnese Panzera & Charles C. Taylor (2018) <doi:10.1080/01621459.2017.1421542>.

Version:	1.1.0
Depends:	R (≥ 3.3.0)
Imports:	foreach, methods, stats
Suggests:	testthat
Published:	2021-02-05
Author:	Charles C. Taylor [aut], Giovanni Lafratta [aut, cre], Stefania Fensore [aut]
Maintainer:	Giovanni Lafratta <giovanni.lafratta at unich.it>
License:	MIT + file LICENSE
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	nprotreg results

Documentation:

Reference manual:

nprotreg.pdf

Downloads:

Package source:	nprotreg_1.1.0.tar.gz
Windows binaries:	r-devel: nprotreg_1.1.0.zip, r-release: nprotreg_1.1.0.zip, r-oldrel: nprotreg_1.1.0.zip
macOS binaries:	r-release (arm64): nprotreg_1.1.0.tgz, r-oldrel (arm64): nprotreg_1.1.0.tgz, r-release (x86_64): nprotreg_1.1.0.tgz, r-oldrel (x86_64): nprotreg_1.1.0.tgz
Old sources:	nprotreg archive

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