getLogScore

Estimation, prediction, and simulation of nonstationary Gaussian process with modular covariate-based covariance functions.
Sources of nonstationarity, such as spatial mean, variance, geometric anisotropy, smoothness, and nugget, can be considered based on spatial characteristics.
An induced compact-supported nonstationary covariance function is provided, enabling fast and memory-efficient computations when handling densely sampled domains.

Federico Blasi

cocons

Covariate-Based Covariance Functions for Nonstationary Spatial
Modeling

Reinhard Furrer

getLogScore function

<dl><dt>z.pred</dt>
<dd><code>(numeric vector)</code>.</dd>
<dt>mean.pred</dt>
<dd><code>(numeric vector)</code>.</dd>
<dt>sd.pred</dt>
<dd><code>(numeric vector)</code>.</dd></dl>

Arguments

Author

Based on a set of predictions computes the Log-Score — getLogScore

<dl>

<dt>z.pred</dt>
<dd><code>(numeric vector)</code>.</dd>


<dt>mean.pred</dt>
<dd><code>(numeric vector)</code>.</dd>


<dt>sd.pred</dt>
<dd><code>(numeric vector)</code>.</dd>

</dl>

getLogScore: Based on a set of predictions computes the Log-Score

Description

Usage

Value

Arguments

Author

References