calcIJ

<code>calcIJ</code> is an internal auxiliary function that calculates a
 unique pair of identifiers for each slave process, corresponding to
 the row and column of the block assigned to the slave process (things
 are more complicated when the block replication factor, \(h\), is
 greater than one).

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

calcIJ function

<dl> <dt>D</dt>
<dd>a positive integer, the partition factor.</dd> </dl>

Arguments

Calculate Slave Process Identifiers — calcIJ

<dl>

 <dt>D</dt>
<dd>a positive integer, the partition factor.</dd>

 </dl>

calcIJ: Calculate Slave Process Identifiers

Description

Usage

Arguments