Distributes Gaussian process calculations across nodes in a distributed memory setting, using Rmpi. The bigGP class provides high-level methods for maximum likelihood with normal data, prediction, calculation of uncertainty (i.e., posterior covariance calculations), and simulation of realizations. In addition, bigGP provides an API for basic matrix calculations with distributed covariance matrices, including Cholesky decomposition, back/forwardsolve, crossproduct, and matrix multiplication.
| Version: | 0.1-7 |
| Depends: | R (≥ 3.0.0), Rmpi (≥ 0.6-2), methods |
| Suggests: | rlecuyer, fields |
| OS_type: | unix |
| Published: | 2021-10-30 |
| Author: | Christopher Paciorek [aut, cre], Benjamin Lipshitz [aut], Prabhat [ctb], Cari Kaufman [ctb], Tina Zhuo [ctb], Rollin Thomas [ctb] |
| Maintainer: | Christopher Paciorek <paciorek at stat.berkeley.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://doi.org/10.18637/jss.v063.i10 |
| NeedsCompilation: | yes |
| SystemRequirements: | OpenMPI or MPICH2 |
| Citation: | bigGP citation info |
| Materials: | README NEWS INSTALL |
| CRAN checks: | bigGP results |
| Reference manual: | bigGP.pdf |
| Package source: | bigGP_0.1-7.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available |
| Old sources: | bigGP archive |
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