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netcmc  

Spatio-Network Generalised Linear Mixed Models for Areal Unit and Network Data
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("netcmc", "1.0.2")



Attach the package and use:
library("netcmc")
Maintained by
George Gerogiannis
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-02-07
Latest Update: 2022-11-08
Description:
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) ). Network structures are modelled by a set of random effects that reflect a multiple membership structure (Browne et al. (2001) ).
How to cite:
George Gerogiannis (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/web/packages/netcmc. Accessed 21 Nov. 2024.
Previous versions and publish date:
1.0.1 (2022-06-29 02:20), 1.0 (2022-02-07 13:00)
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