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bigGP (version 0.1-2)
Distributed Gaussian process calculations
Description
bigGP distributes Gaussian process calculations across
nodes in a distributed memory setting, using Rmpi. The 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.