magp
Mapping-Based Additive Gaussian Process Models
Fits mapping-based additive Gaussian process models for experiments in which each component has both a quantitative level and a position in an ordered sequence. Two model structures are available: a compact two-dimensional mapping and a full mapping with one fewer dimension than the number of components. Both models support parameter estimation, point prediction, and plug-in predictive uncertainty. Input checks validate the sequence data and apply consistent scaling to the quantitative inputs. Computationally intensive covariance and gradient calculations are implemented in C++ with 'Rcpp'. The model was introduced by Xiao et al. (2024) <doi:10.1080/01621459.2022.2123335>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.8.0 |
rolling linux/jammy R-4.5 | magp_0.8.0.tar.gz |
220.2 KiB |
0.8.0 |
rolling linux/noble R-4.5 | magp_0.8.0.tar.gz |
221.5 KiB |
0.8.0 |
rolling source/ R- | magp_0.8.0.tar.gz |
130.7 KiB |
0.8.0 |
latest linux/jammy R-4.5 | magp_0.8.0.tar.gz |
220.2 KiB |
0.8.0 |
latest linux/noble R-4.5 | magp_0.8.0.tar.gz |
221.5 KiB |
0.8.0 |
latest source/ R- | magp_0.8.0.tar.gz |
130.7 KiB |
0.8.0 |
2026-04-23 source/ R- | magp_0.8.0.tar.gz |
0 B |