summary.metric_graph

Function providing a summary of several informations/characteristics of a metric graph object.

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

summary.metric_graph function

<dl><dt>object</dt>
<dd>an object of class <code>metric_graph</code>.</dd>
<dt>messages</dt>
<dd>Should message explaining how to build the results be given for missing quantities?</dd>
<dt>compute_characteristics</dt>
<dd>Should the characteristics of the graph be computed? If <code>NULL</code> it will be determined based on the size of the graph.</dd>
<dt>check_euclidean</dt>
<dd>Check if the graph has Euclidean edges? If <code>NULL</code> it will be determined based on the size of the graph.</dd>
<dt>check_distance_consistency</dt>
<dd>Check the distance consistency assumption?#' If <code>NULL</code> it will be determined based on the size of the graph.</dd>
<dt>...</dt>
<dd>not used.</dd></dl>

Arguments

Summary Method for metric_graph Objects — summary.metric_graph

<dl>

<dt>object</dt>
<dd>an object of class <code>metric_graph</code>.</dd>


<dt>messages</dt>
<dd>Should message explaining how to build the results be given for missing quantities?</dd>


<dt>compute_characteristics</dt>
<dd>Should the characteristics of the graph be computed? If <code>NULL</code> it will be determined based on the size of the graph.</dd>


<dt>check_euclidean</dt>
<dd>Check if the graph has Euclidean edges? If <code>NULL</code> it will be determined based on the size of the graph.</dd>


<dt>check_distance_consistency</dt>
<dd>Check the distance consistency assumption?#' If <code>NULL</code> it will be determined based on the size of the graph.</dd>


<dt>...</dt>
<dd>not used.</dd>

</dl>

summary.metric_graph: Summary Method for `metric_graph` Objects

Description

Usage

Value

Arguments