autoplot

autoplot.sandwich.model

Plot the estimated mean and standard error for each reporting unit.

Spatial prediction is a common practice in social and environmental science. This package enables the implementation of SSH-based spatial prediction proposed by Wang et al. (2013) <doi:10.1068/a44710>. It provides functions to (1) evaluate stratification schemes, (2) interpolate sampling data over user-defined reporting units, (3) assess prediction uncertainties, and (4) evaluate overall accuracy using the k-fold cross-validation estimate.

Yue Lin 

sandwichr

Spatial Prediction Based on Spatial Stratified Heterogeneity

Chengdong Xu 

Jinfeng Wang 

autoplot function

<dl><dt>object</dt>
<dd>A <code>sandwich.model</code> object generated by <code>sandwich.model</code>.</dd>
<dt>titles</dt>
<dd>A list of texts for the titles.</dd>
<dt>labels</dt>
<dd>A list of texts for the legend labels.</dd>
<dt>border_color</dt>
<dd>Color for outlines of the polygons.</dd>
<dt>poly_fill_mean</dt>
<dd>A list of colors for low and high ends of the gradient in the mapping of means.</dd>
<dt>poly_fill_se</dt>
<dd>A list of colors for low and high ends of the gradient in the mapping of standard errors.</dd>
<dt>...</dt>
<dd>Ignored.</dd></dl>

Arguments

Plot prediction results — autoplot

<dl>

<dt>object</dt>
<dd>A <code>sandwich.model</code> object generated by <code>sandwich.model</code>.</dd>


<dt>titles</dt>
<dd>A list of texts for the titles.</dd>


<dt>labels</dt>
<dd>A list of texts for the legend labels.</dd>


<dt>border_color</dt>
<dd>Color for outlines of the polygons.</dd>


<dt>poly_fill_mean</dt>
<dd>A list of colors for low and high ends of the gradient in the mapping of means.</dd>


<dt>poly_fill_se</dt>
<dd>A list of colors for low and high ends of the gradient in the mapping of standard errors.</dd>


<dt>...</dt>
<dd>Ignored.</dd>

</dl>

autoplot: Plot prediction results

Description

Usage

Value

Arguments

References

See Also

Examples