getCIs

Compute approximate confidence intervals for a (fitted) coco object.

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

getCIs function

<dl><dt>coco.object</dt>
<dd><code>(S4)</code> a fitted coco S4 object.</dd>
<dt>inv.hess</dt>
<dd><code>(matrix)</code> Inverse of the Hessian. getHessian.</dd>
<dt>alpha</dt>
<dd><code>(numeric)</code> confidence level.</dd></dl>

Arguments

Author

Compute approximate confidence intervals for a coco object — getCIs

<dl>

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


<dt>inv.hess</dt>
<dd><code>(matrix)</code> Inverse of the Hessian. getHessian.</dd>


<dt>alpha</dt>
<dd><code>(numeric)</code> confidence level.</dd>

</dl>

getCIs: Compute approximate confidence intervals for a coco object

Description

Usage

Value

Arguments

Author