Reminder, have to create an example. This will be exported
after we submit the paper for publication.

Provides functions to estimate, predict and interpolate areal
data. For estimation and prediction we assume areal data is an average
of an underlying continuous spatial process as in Moraga et
al. (2017) <doi:10.1016/j.spasta.2017.04.006>, Johnson et al. (2020)
<doi:10.1186/s12942-020-00200-w>, and Wilson and Wakefield (2020)
<doi:10.1093/biostatistics/kxy041>. The interpolation methodology is
(mostly) based on Goodchild and Lam (1980, ISSN:01652273).

Lucas da Cunha Godoy

smile

Spatial Misalignment: Interpolation, Linkage, and Estimation

vdl function

<dl><dt>coords_sf</dt>
<dd><code>sf</code> POINT target dataset.</dd>
<dt>areal_sf</dt>
<dd><code>sf</code> POLYGON source dataset.</dd>
<dt>vars</dt>
<dd>a <code>character</code> representing the variables (observed at the
source - polygon) to be estimated at the target data.</dd>
<dt>buff</dt>
<dd>scalar <code>numeric</code>. Mostly for internal use.</dd></dl>

Arguments

Voronoi Data Linkage — vdl

<dl>

<dt>coords_sf</dt>
<dd><code>sf</code> POINT target dataset.</dd>


<dt>areal_sf</dt>
<dd><code>sf</code> POLYGON source dataset.</dd>


<dt>vars</dt>
<dd>a <code>character</code> representing the variables (observed at the
source - polygon) to be estimated at the target data.</dd>


<dt>buff</dt>
<dd>scalar <code>numeric</code>. Mostly for internal use.</dd>

</dl>

vdl: Voronoi Data Linkage

Description

Usage

Value

Arguments