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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>.
Package details |
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Author | Charles C. Taylor [aut], Giovanni Lafratta [aut, cre], Stefania Fensore [aut] |
Maintainer | Giovanni Lafratta <giovanni.lafratta@unich.it> |
License | MIT + file LICENSE |
Version | 1.1.1 |
Package repository | View on CRAN |
Installation |
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