getHessian

numerically approximate the Hessian. Hessians of parameters based on "pml" are based on full likelihoods.

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

getHessian function

<dl><dt>coco.object</dt>
<dd><code>(S4)</code> a fitted coco object.</dd>
<dt>ncores</dt>
<dd><code>(integer)</code> number of cores used for the computation.</dd>
<dt>eps</dt>
<dd><code>(numeric)</code> ...</dd></dl>

Arguments

Author

getHessian — getHessian

<dl>

<dt>coco.object</dt>
<dd><code>(S4)</code> a fitted coco object.</dd>


<dt>ncores</dt>
<dd><code>(integer)</code> number of cores used for the computation.</dd>


<dt>eps</dt>
<dd><code>(numeric)</code> ...</dd>

</dl>

getHessian: getHessian

Description

Usage

Value

Arguments

Author