order_middleout

Return the ordering of locations increasing in their
distance to the average location

Functions for fitting and doing predictions with
Gaussian process models using Vecchia's (1988) approximation.
Package also includes functions for reordering input locations,
finding ordered nearest neighbors (with help from 'FNN' package),
grouping operations, and conditional simulations.
Covariance functions for spatial and spatial-temporal data
on Euclidean domains and spheres are provided. The original
approximation is due to Vecchia (1988)
<http://www.jstor.org/stable/2345768>, and the reordering and
grouping methods are from Guinness (2018)
<doi:10.1080/00401706.2018.1437476>.
Model fitting employs a Fisher scoring algorithm described
in Guinness (2019) <doi:10.48550/arXiv.1905.08374>.

Joseph Guinness

GpGp

Fast Gaussian Process Computation Using Vecchia's Approximation

Matthias Katzfuss

Youssef Fahmy

order_middleout function

<dl><dt>locs</dt>
<dd>A matrix of locations. Each row of <code>locs</code> contains a location, which can
be a point in Euclidean space R^d, a point in space-time R^d x T, 
a longitude and latitude (in degrees) giving a point on the sphere, 
or a longitude, latitude, and time giving a point in the sphere-time domain.</dd>
<dt>lonlat</dt>
<dd>TRUE/FALSE whether locations are longitudes and latitudes.</dd></dl>

Arguments

Middle-out ordering — order_middleout

<dl>

<dt>locs</dt>
<dd>A matrix of locations. Each row of <code>locs</code> contains a location, which can
be a point in Euclidean space R^d, a point in space-time R^d x T, 
a longitude and latitude (in degrees) giving a point on the sphere, 
or a longitude, latitude, and time giving a point in the sphere-time domain.</dd>


<dt>lonlat</dt>
<dd>TRUE/FALSE whether locations are longitudes and latitudes.</dd>

</dl>

order_middleout: Middle-out ordering

Description

Usage

Value

Arguments

Examples