orderCoordinatesMMD

<code>orderCoordinatesMMD</code> orders an array of (x,y) spatial coordinates
according to the "maximum minimum distance" (MMD), as described in Guinness,
2018. (Points are selected to maximize their minimum distance to already-
selected points).

Enables off-the-shelf functionality for fully Bayesian, nonstationary Gaussian process modeling. The approach to nonstationary modeling involves a closed-form, convolution-based covariance function with spatially-varying parameters; these parameter processes can be specified either deterministically (using covariates or basis functions) or stochastically (using approximate Gaussian processes). Stationary Gaussian processes are a special case of our methodology, and we furthermore implement approximate Gaussian process inference to account for very large spatial data sets (Finley, et al (2017) <doi:10.48550/arXiv.1702.00434>). Bayesian inference is carried out using Markov chain Monte Carlo methods via the "nimble" package, and posterior prediction for the Gaussian process at unobserved locations is provided as a post-processing step.

Daniel Turek

BayesNSGP

Bayesian Analysis of Non-Stationary Gaussian Process Models

Mark Risser

orderCoordinatesMMD function

<dl><dt>coords</dt>
<dd>N x 2 array of N 2-dimensional (x,y) spatial coordinates.</dd>
<dt>exact</dt>
<dd>Logical; <code>FALSE</code> uses a fast approximation to MMD ordering
(and is almost always recommended), while <code>TRUE</code> uses exact MMD
ordering but is infeasible for large number of locations.</dd></dl>

Arguments

Order coordinates according to a maximum-minimum distance criterion. — orderCoordinatesMMD

<dl>

<dt>coords</dt>
<dd>N x 2 array of N 2-dimensional (x,y) spatial coordinates.</dd>


<dt>exact</dt>
<dd>Logical; <code>FALSE</code> uses a fast approximation to MMD ordering
(and is almost always recommended), while <code>TRUE</code> uses exact MMD
ordering but is infeasible for large number of locations.</dd>

</dl>

orderCoordinatesMMD: Order coordinates according to a maximum-minimum distance criterion.

Description

Usage

Value

Arguments

Examples