getDesignMatrix

Creates a unique design matrix based on model specification for
each of the different potentially spatially varying aspects.

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

getDesignMatrix function

<dl><dt>model.list</dt>
<dd><code>(list)</code> a list of formulas, one for each source of nonstationarity, specifying the
models.</dd>
<dt>data</dt>
<dd><code>(data.frame)</code> a data.frame.</dd></dl>

Arguments

Author

Create an efficient design matrix based on a list of aspect models — getDesignMatrix

<dl>

<dt>model.list</dt>
<dd><code>(list)</code> a list of formulas, one for each source of nonstationarity, specifying the
models.</dd>


<dt>data</dt>
<dd><code>(data.frame)</code> a data.frame.</dd>

</dl>

getDesignMatrix: Create an efficient design matrix based on a list of aspect models

Description

Usage

Value

Arguments

Author