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Distributes Gaussian process calculations across nodes in a distributed memory setting, using Rmpi. The bigGP class provides highlevel 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.
Package details 


Author  Christopher Paciorek [aut, cre], Benjamin Lipshitz [aut], Prabhat [ctb], Cari Kaufman [ctb], Tina Zhuo [ctb], Rollin Thomas [ctb] 
Maintainer  Christopher Paciorek <[email protected]> 
License  GPL (>= 2) 
Version  0.16 
URL  http://www.jstatsoft.org/v63/i10/ 
Package repository  View on CRAN 
Installation 
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