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: 1.0.0
Depends: R (≥ 3.3.0)
Imports: methods, expm, stats
Suggests: testthat
Published: 2018-10-14
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

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Reference manual: nprotreg.pdf
Package source: nprotreg_1.0.0.tar.gz
Windows binaries: r-devel: nprotreg_1.0.0.zip, r-release: nprotreg_1.0.0.zip, r-oldrel: nprotreg_1.0.0.zip
macOS binaries: r-release: nprotreg_1.0.0.tgz, r-oldrel: nprotreg_1.0.0.tgz

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