distributedKrigeProblem-class

distributedKrigeProblem

<p><code>distributedKrigeProblem</code> contains the distributed components of
  the core vectors and matrices of the krigeProblem class, as well as
  copies of the functions for calculating mean vectors and covariance
  matrices, parameter values, and information about the pieces of the
  distributed objects contained on a given slave process. The only
  method associated with the ReferenceClass is a constructor.</p>

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.

Christopher Paciorek

bigGP

Distributed Gaussian Process Calculations

Benjamin Lipshitz

 Prabhat

Cari Kaufman

Tina Zhuo

Rollin Thomas

distributedKrigeProblem-class function

ReferenceClass for Distributed Components of the krigeProblem ReferenceClass — distributedKrigeProblem-class

ReferenceClass for Distributed Components of the krigeProblem ReferenceClass

distributedKrigeProblem-class: ReferenceClass for Distributed Components of the krigeProblem ReferenceClass

Description

Arguments

See Also