getMatCov

This function takes the entire covariance matrix and creates
a matrix of covariances based on the vecchia approximatino object

Fast scalable Gaussian process approximations, particularly well suited to spatial (aerial, remote-sensed) and environmental data, described in more detail in Katzfuss and Guinness (2017) <arXiv:1708.06302>. Package also contains a fast implementation of the incomplete Cholesky decomposition (IC0), based on Schaefer et al. (2019) <arXiv:1706.02205> and MaxMin ordering proposed in Guinness (2018) <arXiv:1609.05372>.

Marcin Jurek

GPvecchia

Scalable Gaussian-Process Approximations

Matthias Katzfuss

Daniel Zilber

Wenlong Gong

Joe Guinness

Jingjie Zhang

Florian Schaefer

getMatCov function

<dl><dt>V</dt>
<dd>the object returned by vecchia_specify</dd>
<dt>covariances</dt>
<dd>The full covariance matrix or a covariance function</dd>
<dt>factor</dt>
<dd>True if we are passing a factor of a matrix</dd></dl>

Arguments

extract the required elements from the covariance matrix — getMatCov

<dl>

<dt>V</dt>
<dd>the object returned by vecchia_specify</dd>


<dt>covariances</dt>
<dd>The full covariance matrix or a covariance function</dd>


<dt>factor</dt>
<dd>True if we are passing a factor of a matrix</dd>

</dl>

getMatCov: extract the required elements from the covariance matrix

Description

Usage

Value

Arguments