plot.graph_bru_proc_pred

Auxiliary function to obtain plots of the processed predictions of the field
using 'inlabru'.

Facilitates creation and manipulation of metric graphs, such as street or river networks. Further facilitates operations and visualizations of data on metric graphs, and the creation of a large class of random fields and stochastic partial differential equations on such spaces. These random fields can be used for simulation, prediction and inference. In particular, linear mixed effects models including random field components can be fitted to data based on computationally efficient sparse matrix representations. Interfaces to the R packages 'INLA' and 'inlabru' are also provided, which facilitate working with Bayesian statistical models on metric graphs. The main references for the methods are Bolin, Simas and Wallin (2024) <doi:10.3150/23-BEJ1647>, Bolin, Kovacs, Kumar and Simas (2023) <doi:10.1090/mcom/3929> and Bolin, Simas and Wallin (2023) <doi:10.48550/arXiv.2304.03190> and <doi:10.48550/arXiv.2304.10372>.

David Bolin

MetricGraph

Random Fields on Metric Graphs

Alexandre Simas

Jonas Wallin

plot.graph_bru_proc_pred function

<dl><dt>x</dt>
<dd>A processed predicted object obtained with the <code>process_rspde_predictions</code> function.</dd>
<dt>y</dt>
<dd>Not used.</dd>
<dt>vertex_size</dt>
<dd>Size of the vertices.</dd>
<dt>...</dt>
<dd>Additional parameters to be passed to plot_function.</dd></dl>

Arguments

Plot of processed predicted values with 'inlabru' — plot.graph_bru_proc_pred

<dl>

<dt>x</dt>
<dd>A processed predicted object obtained with the <code>process_rspde_predictions</code> function.</dd>


<dt>y</dt>
<dd>Not used.</dd>


<dt>vertex_size</dt>
<dd>Size of the vertices.</dd>


<dt>...</dt>
<dd>Additional parameters to be passed to plot_function.</dd>

</dl>

plot.graph_bru_proc_pred: Plot of processed predicted values with 'inlabru'

Description

Usage

Value

Arguments