Package: netcmc 1.0.2

George Gerogiannis

netcmc: Spatio-Network Generalised Linear Mixed Models for Areal Unit and Network Data

Implements a class of univariate and multivariate spatio-network generalised linear mixed models for areal unit and network data, with inference in a Bayesian setting using Markov chain Monte Carlo (MCMC) simulation. The response variable can be binomial, Gaussian, or Poisson. Spatial autocorrelation is modelled by a set of random effects that are assigned a conditional autoregressive (CAR) prior distribution following the Leroux model (Leroux et al. (2000) <doi:10.1007/978-1-4612-1284-3_4>). Network structures are modelled by a set of random effects that reflect a multiple membership structure (Browne et al. (2001) <doi:10.1177/1471082X0100100202>).

Authors:George Gerogiannis, Mark Tranmer, Duncan Lee

netcmc_1.0.2.tar.gz
netcmc_1.0.2.tar.gz(r-4.5-noble)netcmc_1.0.2.tar.gz(r-4.4-noble)
netcmc_1.0.2.tgz(r-4.4-emscripten)netcmc_1.0.2.tgz(r-4.3-emscripten)
netcmc.pdf |netcmc.html✨
netcmc/json (API)

# Install 'netcmc' in R:
install.packages('netcmc', repos = 'https://cloud.r-project.org')
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

1.00 score 170 downloads 10 exports 39 dependencies

Last updated 2 years agofrom:ca5c9511ce. Checks:1 OK, 1 NOTE, 1 ERROR. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 27 2025
R-4.5-linux-x86_64NOTEMar 27 2025
R-4.4-linux-x86_64ERRORMar 27 2025

Exports:getAdjacencyMatrixgetMembershipMatrixgetTotalAltersByStatusmultiNetmultiNetLerouxmultiNetRanduniuniNetuniNetLerouxuniNetRand

Dependencies:clicodacolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixMatrixModelsmcmcMCMCpackmgcvmunsellmvtnormnlmepillarpkgconfigquantregR6RColorBrewerRcppRcppArmadilloRcppProgressrlangscalesSparseMsurvivaltibbleutf8vctrsviridisLitewithr

Citation

To cite package ‘netcmc’ in publications use:

Gerogiannis G, Tranmer M, Lee D (2022). netcmc: Spatio-Network Generalised Linear Mixed Models for Areal Unit and Network Data. R package version 1.0.2, https://CRAN.R-project.org/package=netcmc.

ATTENTION: This citation information has been auto-generated from the package DESCRIPTION file and may need manual editing, see ‘help("citation")’.

Corresponding BibTeX entry: 

  @Manual{,
    title = {netcmc: Spatio-Network Generalised Linear Mixed Models for
      Areal Unit and Network Data},
    author = {George Gerogiannis and Mark Tranmer and Duncan Lee},
    year = {2022},
    note = {R package version 1.0.2},
    url = {https://CRAN.R-project.org/package=netcmc},
  }