Distributed Gaussian Process Calculations R package bigGP version 0.1.9 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. Software Depends: R (>= 3.0.0), Rmpi (>= 0.6-2), methods Suggests: rlecuyer, fields Christopher Paciorek <paciorek@stat.berkeley.edu> Comprehensive R Archive Network (CRAN) Christopher Paciorek [aut, cre], Benjamin Lipshitz [aut], Prabhat [ctb], Cari Kaufman [ctb], Tina Zhuo [ctb], Rollin Thomas [ctb] GPL (>= 2) 2025-04-09 application/tgz https://CRAN.R-project.org/package=bigGP doi:10.32614/CRAN.package.bigGP