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MetricGraph  

Random Fields on Metric Graphs
View on CRAN: Click here


Download and install MetricGraph package within the R console
Install from CRAN:
install.packages("MetricGraph")

Install from Github:
library("remotes")
install_github("cran/MetricGraph")

Install by package version:
library("remotes")
install_version("MetricGraph", "1.3.0")



Attach the package and use:
library("MetricGraph")
Maintained by
David Bolin
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-06-01
Latest Update: 2024-02-27
Description:
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) , Bolin, Kovacs, Kumar and Simas (2023) and Bolin, Simas and Wallin (2023) and .
How to cite:
David Bolin (2023). MetricGraph: Random Fields on Metric Graphs. R package version 1.3.0, https://cran.r-project.org/web/packages/MetricGraph
Previous versions and publish date:
1.1.1 (2023-06-01 14:00), 1.1.2 (2023-07-04 16:23), 1.2.0 (2023-11-07 11:10)
Other packages that cited MetricGraph R package
View MetricGraph citation profile
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Functions, R codes and Examples using the MetricGraph R package
Full MetricGraph package functions and examples
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