Package: MetricGraph 1.3.0.9000

MetricGraph: Random Fields on Metric Graphs

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>.

Authors:David Bolin [cre, aut], Alexandre Simas [aut], Jonas Wallin [aut]

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MetricGraph.pdf |MetricGraph.html✨
MetricGraph/json (API)
NEWS

# Install 'MetricGraph' in R:
install.packages('MetricGraph', repos = c('https://davidbolin.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/davidbolin/metricgraph/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • pems - Traffic speed data from San Jose, California
  • pems_repl - Traffic speed data with replicates from San Jose, California

On CRAN:

32 exports 11 stars 2.57 score 56 dependencies 272 scripts 221 downloads

Last updated 16 days agofrom:de3d0688a4. Checks:ERROR: 1 WARNING: 8. Indexed: yes.

TargetResultDate
Doc / VignettesFAILSep 02 2024
R-4.5-win-x86_64WARNINGSep 02 2024
R-4.5-linux-x86_64WARNINGSep 02 2024
R-4.4-win-x86_64WARNINGSep 02 2024
R-4.4-mac-x86_64WARNINGSep 02 2024
R-4.4-mac-aarch64WARNINGSep 02 2024
R-4.3-win-x86_64WARNINGSep 02 2024
R-4.3-mac-x86_64WARNINGSep 02 2024
R-4.3-mac-aarch64WARNINGSep 02 2024

Exports:%>%augmentCholeskydrop_naexp_covariancefiltergg_dfglancegraph_bru_process_datagraph_componentsgraph_data_spdegraph_lgcpgraph_lmegraph_spdegraph_spde_basisgraph_spde_make_Agraph_starting_valueslogo_linesmake_Q_eulermake_Q_spacetimemetric_graphmutateposterior_crossvalidationsample_spdeselectsimulate_spacetimespde_covariancespde_metric_graph_resultspde_precisionspde_variancesummariset

Dependencies:backportsbroomclassclassIntclicolorspacecpp11DBIdplyre1071fansifarverfmeshergenericsggnewscaleggplot2gluegtableigraphisobandKernSmoothlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigproxypurrrR6RColorBrewerRcppRcppEigenrlangrSPDEs2scalessfspstringistringrtibbletidyrtidyselectunitsutf8vctrsviridisLitewithrwkzoo

Readme and manuals

Help Manual

Help pageTopics
Gaussian processes on metric graphsMetricGraph-package MetricGraph
Augment data with information from a 'graph_lme' objectaugment augment.graph_lme
Metric graph 'inlabru' mapperbru_get_mapper.inla_metric_graph_spde bru_mapper.inla_metric_graph_spde ibm_jacobian.bru_mapper_inla_metric_graph_spde ibm_n.bru_mapper_inla_metric_graph_spde ibm_values.bru_mapper_inla_metric_graph_spde
A version of 'tidyr::drop_na()' function for datasets on metric graphsdrop_na drop_na.metric_graph_data
Exponential covariance functionexp_covariance
A version of 'dplyr::filter()' function for datasets on metric graphsfilter filter.metric_graph_data
Data frame for metric_graph_spde_result objects to be used in 'ggplot2'gg_df gg_df.metric_graph_spde_result
Glance at a 'graph_lme' objectglance glance.graph_lme
Prepare data frames or data lists to be used with 'inlabru' in metric graphsgraph_bru_process_data
Connected components of metric graphgraph_components
Data extraction for 'spde' modelsgraph_data_spde
Simulation of log-Gaussian Cox processes driven by Whittle-Matérn fields on metric graphsgraph_lgcp
Metric graph linear mixed effects modelsgraph_lme
'INLA' implementation of Whittle-Matérn fields for metric graphsgraph_spde
Deprecated - Observation/prediction matrices for 'SPDE' modelsgraph_spde_basis
Deprecated - Observation/prediction matrices for 'SPDE' modelsgraph_spde_make_A
Starting values for random field models on metric graphsgraph_starting_values
Create lines for package namelogo_lines
Space-time precision operator Euler discretizationmake_Q_euler
Space-time precision operator discretizationmake_Q_spacetime
Metric graphmetric_graph
A version of 'dplyr::mutate()' function for datasets on metric graphsmutate mutate.metric_graph_data
Traffic speed data from San Jose, Californiapems
Traffic speed data with replicates from San Jose, Californiapems_repl
Plot of predicted values with 'inlabru'plot.graph_bru_pred
Leave-one-out crossvalidation for 'graph_lme' models assuming observations at the vertices of metric graphsposterior_crossvalidation
Prediction for a mixed effects regression model on a metric graphpredict.graph_lme
Predict method for 'inlabru' fits on Metric Graphspredict.inla_metric_graph_spde
Predict method for 'inlabru' fits on Metric Graphs for 'rSPDE' modelspredict.rspde_metric_graph
Samples a Whittle-Matérn field on a metric graphsample_spde
A version of 'dplyr::select()' function for datasets on metric graphsselect select.metric_graph_data
space-time simulation based on implicit Euler discretization in timesimulate_spacetime
Simulation of models on metric graphssimulate.graph_lme
Covariance function for Whittle-Matérn fieldsspde_covariance
Metric graph SPDE result extraction from 'INLA' estimation resultsspde_metric_graph_result
Precision matrix for Whittle-Matérn fieldsspde_precision
Variancefor Whittle-Matérn fieldsspde_variance
A version of 'dplyr::summarise()' function for datasets on metric graphssummarise summarise.metric_graph_data
Summary Method for 'graph_lme' Objectssummary.graph_lme
Summary Method for 'metric_graph' Objectssummary.metric_graph
Summary for posteriors of field parameters for an 'inla_rspde' model from a 'rspde.result' objectsummary.metric_graph_spde_result