Package: nprotreg 1.1.1

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>.

Authors:Charles C. Taylor [aut], Giovanni Lafratta [aut, cre], Stefania Fensore [aut]

nprotreg_1.1.1.tar.gz
nprotreg_1.1.1.zip(r-4.5)nprotreg_1.1.1.zip(r-4.4)nprotreg_1.1.1.zip(r-4.3)
nprotreg_1.1.1.tgz(r-4.4-any)nprotreg_1.1.1.tgz(r-4.3-any)
nprotreg_1.1.1.tar.gz(r-4.5-noble)nprotreg_1.1.1.tar.gz(r-4.4-noble)
nprotreg_1.1.1.tgz(r-4.4-emscripten)nprotreg_1.1.1.tgz(r-4.3-emscripten)
nprotreg.pdf |nprotreg.html
nprotreg/json (API)
NEWS

# Install 'nprotreg' in R:
install.packages('nprotreg', repos = c('https://novacta.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

9 exports 1 stars 0.23 score 3 dependencies 34 scripts 1.0k downloads

Last updated 12 months agofrom:687a26f2a1. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 22 2024
R-4.5-winOKAug 22 2024
R-4.5-linuxOKAug 22 2024
R-4.4-winOKAug 22 2024
R-4.4-macOKAug 22 2024
R-4.3-winOKAug 22 2024
R-4.3-macOKAug 22 2024

Exports:convert_cartesian_to_sphericalconvert_spherical_to_cartesiancross_validate_concentrationfit_regressionget_equally_spaced_pointsget_skew_symmetric_matrixsimulate_regressionsimulate_rigid_regressionweight_explanatory_points

Dependencies:codetoolsforeachiterators