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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: | 1.1.1 |
Depends: | R (≥ 3.3.0) |
Imports: | foreach, methods, stats |
Suggests: | testthat |
Published: | 2023-09-28 |
DOI: | 10.32614/CRAN.package.nprotreg |
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 |
Reference manual: | nprotreg.pdf |
Package source: | nprotreg_1.1.1.tar.gz |
Windows binaries: | r-devel: nprotreg_1.1.1.zip, r-release: nprotreg_1.1.1.zip, r-oldrel: nprotreg_1.1.1.zip |
macOS binaries: | r-release (arm64): nprotreg_1.1.1.tgz, r-oldrel (arm64): nprotreg_1.1.1.tgz, r-release (x86_64): nprotreg_1.1.1.tgz, r-oldrel (x86_64): nprotreg_1.1.1.tgz |
Old sources: | nprotreg archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.