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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1.1 |
rolling linux/jammy R-4.5 | nprotreg_1.1.1.tar.gz |
502.9 KiB |
1.1.1 |
rolling linux/noble R-4.5 | nprotreg_1.1.1.tar.gz |
502.8 KiB |
1.1.1 |
rolling source/ R- | nprotreg_1.1.1.tar.gz |
160.4 KiB |
1.1.1 |
latest linux/jammy R-4.5 | nprotreg_1.1.1.tar.gz |
502.9 KiB |
1.1.1 |
latest linux/noble R-4.5 | nprotreg_1.1.1.tar.gz |
502.8 KiB |
1.1.1 |
latest source/ R- | nprotreg_1.1.1.tar.gz |
160.4 KiB |
1.1.1 |
2026-04-26 source/ R- | nprotreg_1.1.1.tar.gz |
160.4 KiB |
1.1.1 |
2026-04-23 source/ R- | nprotreg_1.1.1.tar.gz |
160.4 KiB |
1.1.1 |
2026-04-09 windows/windows R-4.5 | nprotreg_1.1.1.zip |
503.9 KiB |
1.1.1 |
2025-04-20 source/ R- | nprotreg_1.1.1.tar.gz |
160.4 KiB |