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
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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)

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10 exports 0.00 score 39 dependencies 1 scripts 268 downloads

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

Exports:getAdjacencyMatrixgetMembershipMatrixgetTotalAltersByStatusmultiNetmultiNetLerouxmultiNetRanduniuniNetuniNetLerouxuniNetRand

Dependencies:clicodacolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixMatrixModelsmcmcMCMCpackmgcvmunsellmvtnormnlmepillarpkgconfigquantregR6RColorBrewerRcppRcppArmadilloRcppProgressrlangscalesSparseMsurvivaltibbleutf8vctrsviridisLitewithr