ex_data_2D

A dataset containing spatially distributed CO2 efflux levels as a dependent
variable and temperature as an independent variables within CONUS.

datasets

Implementation of the autocorrelated conditioned Latin
Hypercube Sampling (acLHS) algorithm for 1D (time-series) and 2D (spatial)
data. The acLHS algorithm is an extension of the conditioned Latin Hypercube
Sampling (cLHS) algorithm that allows sampled data to have similar
correlative and statistical features of the original data. Only a properly
formatted dataframe needs to be provided to yield subsample indices from
the primary function. For more details about the cLHS algorithm, see Minasny
and McBratney (2006), <doi:10.1016/j.cageo.2005.12.009>. For acLHS, see Le
and Vargas (2024) <doi:10.1016/j.cageo.2024.105539>.

Gabriel Laboy

aclhs

Autocorrelated Conditioned Latin Hypercube Sampling

Van Huong Le

Rodrigo Vargas

ex_data_2D function

<div class="section" id="ex-data-d">
<h3><code>ex_data_2D</code></h3>
A data frame with 903 rows and 4 columns:<dl>
<dt>X</dt>
<dd>The longitude</dd><dt>Y</dt>
<dd>The latitude</dd><dt>rTemp</dt>
<dd>The temperature</dd><dt>rRS</dt>
<dd>The carbon dioxide efflux</dd>
</dl>tools:::Rd_expr_doi("10.1111/gcb.15666")
</div>

Format

Spatial Distribution of Soil CO2 Efflux for CONUS — ex_data_2D

<div class='section' id='ex-data-d'>
<h3><code>ex_data_2D</code></h3>


A data frame with 903 rows and 4 columns:<dl>
<dt>X</dt>
<dd>The longitude</dd>

<dt>Y</dt>
<dd>The latitude</dd>

<dt>rTemp</dt>
<dd>The temperature</dd>

<dt>rRS</dt>
<dd>The carbon dioxide efflux</dd>


</dl>tools:::Rd_expr_doi("10.1111/gcb.15666")
</div>

ex_data_2D: Spatial Distribution of Soil CO2 Efflux for CONUS

Description

Usage

Arguments

Format

`ex_data_2D`

Examples