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>.
|Author||Charles C. Taylor [aut], Giovanni Lafratta [aut, cre], Stefania Fensore [aut]|
|Maintainer||Giovanni Lafratta <email@example.com>|
|License||MIT + file LICENSE|
|Package repository||View on CRAN|
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