latentnet: mcmc.diagnostics.ergmm – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

mcmc.diagnostics.ergmm

Conduct MCMC diagnostics on an ERGMM fit

Description

This function creates simple diagnostic plots for the MCMC sampled statistics produced from a fit. It also prints the Raftery-Lewis diagnostics, indicates if they are sufficient, and suggests the run length required.

Usage

## S3 method for class 'ergmm'
mcmc.diagnostics(
  object,
  which.diags = c("cor", "acf", "trace", "raftery"),
  burnin = FALSE,
  which.vars = NULL,
  vertex.i = c(1),
  ...
)

Arguments

`object`	An object of class `ergmm`.
`which.diags`	A list of diagnostics to produce. "cor" is the correlation matrix of the statistics, "acf" plots the autocorrelation functions, "trace" produces trace plots and density estimates, and "raftery" produces the Raftery-Lewis statistics.
`burnin`	If not `FALSE`, rather than perform diagnostics on the sampling run, performs them on the pilot run whose index is given.
`which.vars`	A named list mapping variable names to the indices to include. If given, overrides the defaults and all arguments that follow.
`vertex.i`	A numeric vector of vertices whose latent space coordinates and random effects to include.
`...`	Additional arguments. None are supported at the moment.

Details

Produces the plots per which.diags. Autocorrelation function that is printed if "acf" is requested is for lags 0 and interval.

Value

mcmc.diagnostics.ergmm returns a table of Raftery-Lewis diagnostics.

Examples

#
data(sampson)
#
# test the mcmc.diagnostics function
#
gest <- ergmm(samplike ~ euclidean(d=2),
              control=ergmm.control(burnin=1000,interval=5))
summary(gest)
#
# Plot the traces and densities
#
mcmc.diagnostics(gest)

latentnet

Latent Position and Cluster Models for Statistical Networks

v2.10.5

GPL-3 + file LICENSE

Authors

Pavel N. Krivitsky [aut, cre] (<https://orcid.org/0000-0002-9101-3362>), Mark S. Handcock [aut], Susan M. Shortreed [ctb], Jeremy Tantrum [ctb], Peter D. Hoff [ctb], Li Wang [ctb], Kirk Li [ctb], Jake Fisher [ctb], Jordan T. Bates [ctb]

Initial release

2020-03-20