vecchia_likelihood

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

vecchia_likelihood function

<dl><dt>z</dt>
<dd>the observed data</dd>
<dt>vecchia.approx</dt>
<dd>a vecchia object as generated by vecchia_specify()</dd>
<dt>covparms</dt>
<dd>covariance parameters as a vector</dd>
<dt>nuggets</dt>
<dd>either a single (constant) nugget or a vector of nugget terms for the observations</dd>
<dt>covmodel</dt>
<dd>covariance model, 'matern' by default</dd></dl>

Arguments

evaluation of the likelihood — vecchia_likelihood

<dl>

<dt>z</dt>
<dd>the observed data</dd>


<dt>vecchia.approx</dt>
<dd>a vecchia object as generated by vecchia_specify()</dd>


<dt>covparms</dt>
<dd>covariance parameters as a vector</dd>


<dt>nuggets</dt>
<dd>either a single (constant) nugget or a vector of nugget terms for the observations</dd>


<dt>covmodel</dt>
<dd>covariance model, 'matern' by default</dd>

</dl>

evaluation of the likelihood

vecchia_likelihood: evaluation of the likelihood

Description

Usage

Value

Arguments

Examples