Dieter William Joenssen, with contributions from Thomas Muellerleile
c(person("Dieter William", "Joenssen", role = c("aut", "cre", "cph"),
email = "Dieter.Joenssen@TU-Ilmenau.de"),
person("Thomas", "Muellerleile", role = "ctb",
email = "Thomas.Muellerleile@TU-Ilmenau.de"))
This package contains seven specialized statistical tests and support functions
for determining if numerical data could conform to Benford's law.

Dieter William Joenssen [aut, cre, cph],
Thomas Muellerleile [ctb]

R (>= 3.0.0), grDevices, graphics, stats
c(person("Dieter William", "Joenssen", role = c("aut", "cre", "cph"),
email = "Dieter.Joenssen@googlemail.com"),
person("Thomas", "Muellerleile", role = "ctb",
email = "Thomas.Muellerleile@TU-Ilmenau.de"))
Several specialized statistical tests and support functions
for determining if numerical data could conform to Benford's law.

Bayesian inference for exponential random graph models
Functions implementing Bayesian estimation for exponential
random graph models via exchange algorithm

Bayesian analysis for exponential random graph models
Set of tools to analyse Bayesian exponential random graph models
network, ergm, coda, KernSmooth, mvtnorm, MASS

Set of tools to analyse Bayesian exponential random graph
models

Alberto Caimo [aut, cre], Nial Friel [ctb]

Bayesian Exponential Random Graph Models
Alberto Caimo [aut, cre],
Lampros Bouranis [aut],
Florian Maire [ctb],
Nial Friel [ctb]
Set of tools to analyse Bayesian exponential random graph models.

network, coda, MCMCpack, Matrix, mvtnorm

Alberto Caimo [aut, cre],
Lampros Bouranis [aut],
Robert Krause [aut]
Nial Friel [ctb]

Bayesian analysis for exponential random graph models using advanced computational algorithms. More information can be found at: <https://acaimo.github.io/Bergm>.
network, coda, MCMCpack, Matrix, mvtnorm, matrixcalc

network, coda, MCMCpack, Matrix, mvtnorm, matrixcalc,
statnet.common

Bayesian analysis for exponential random graph models using advanced computational algorithms. More information can be found at: <https://acaimo.github.io/Bergm/>.