Random Fields on Metric Graphs
Augment data with information from a graph_lme object
Metric graph 'inlabru' mapper
A version of tidyr::drop_na() function for datasets on metric graphs
Exponential covariance function
A version of dplyr::filter() function for datasets on metric graphs
Data frame for metric_graph_spde_result objects to be used in 'ggplot2...
Glance at a graph_lme object
Prepare data frames or data lists to be used with 'inlabru' in metric ...
Connected components of metric graph
Data extraction for 'spde' models
Simulation of log-Gaussian Cox processes driven by Whittle-Matérn fiel...
Metric graph linear mixed effects models
Deprecated - Observation/prediction matrices for 'SPDE' models
Deprecated - Observation/prediction matrices for 'SPDE' models
'INLA' implementation of Whittle-Matérn fields for metric graphs
Starting values for random field models on metric graphs
Create a log-Gaussian Cox process model for metric graphs
Convert a linnet object to a metric graph object
Create lines for package name
Space-time precision operator Euler discretization
Space-time precision operator discretization
Metric graph
Gaussian processes on metric graphs
A version of dplyr::mutate() function for datasets on metric graphs
Pipe operator
Plot of predicted values with 'inlabru'
Plot of processed predicted values with 'inlabru'
Cross-validation for graph_lme models assuming observations at the v...
Prediction for a mixed effects regression model on a metric graph
Predict method for 'inlabru' fits on Metric Graphs
Predict method for 'inlabru' fits on Metric Graphs for 'rSPDE' models
Process predictions of rspde_metric_graph objects obtained by using ...
Convert a psp object to a metric graph object
Samples a Whittle-Matérn field on a metric graph
A version of dplyr::select() function for datasets on metric graphs
Selected Inverse Calculation
space-time simulation based on implicit Euler discretization in time
Simulation of models on metric graphs
Covariance function for Whittle-Matérn fields
Metric graph SPDE result extraction from 'INLA' estimation results
Precision matrix for Whittle-Matérn fields
Variancefor Whittle-Matérn fields
Convert an stlpp object to a metric graph object
A version of dplyr::summarise() function for datasets on metric grap...
Summary Method for graph_lme Objects
Summary for posteriors of field parameters for an inla_rspdemodel fr...
Summary Method for metric_graph Objects
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>.
Useful links