summary.ergm: Summarizing ERGM Model Fits

Description

base::summary() method for ergm() fits.

Usage

# S3 method for ergm
summary(
  object,
  ...,
  correlation = FALSE,
  covariance = FALSE,
  total.variation = TRUE
)
# S3 method for summary.ergm
print(
  x,
  digits = max(3, getOption("digits") - 3),
  correlation = x$correlation,
  covariance = x$covariance,
  signif.stars = getOption("show.signif.stars"),
  eps.Pvalue = 1e-04,
  print.formula = FALSE,
  print.fitinfo = TRUE,
  print.coefmat = TRUE,
  print.message = TRUE,
  print.deviances = TRUE,
  print.drop = TRUE,
  print.offset = TRUE,
  print.call = TRUE,
  ...
)

Value

The returned object is a list of class "ergm.summary" with the following elements:

formula: ERGM model formula
call: R call used to fit the model
correlation, covariance: whether to print correlation/covariance matrices of the estimated parameters
pseudolikelihood: was the model estimated with MPLE
independence: is the model dyad-independent
control: the control.ergm() object used
samplesize: MCMC sample size
message: optional message on the validity of the standard error estimates
null.lik.0: It is TRUE of the null model likelihood has not been calculated. See logLikNull()
devtext, devtable: Deviance type and table
aic, bic: values of AIC and BIC
coefficients: matrices with model parameters and associated statistics
asycov: asymptotic covariance matrix
asyse: asymptotic standard error matrix
offset, drop, estimate, iterations, mle.lik, null.lik: see documentation of the object returned by ergm()

Arguments

object: an object of class ergm, usually, a result of a call to ergm().
...: For summary.ergm() additional arguments are passed to logLik.ergm(). For print.summary.ergm(), to stats::printCoefmat().
correlation: logical; if TRUE, the correlation matrix of the estimated parameters is returned and printed.
covariance: logical; if TRUE, the covariance matrix of the estimated parameters is returned and printed.
total.variation: logical; if TRUE, the standard errors reported in the Std. Error column are based on the sum of the likelihood variation and the MCMC variation. If FALSE only the likelihood variation is used. The \(p\)-values are based on this source of variation.
x: object of class summary.ergm returned by summary.ergm().
digits: significant digits for coefficients
signif.stars: whether to print dots and stars to signify statistical significance. See print.summary.lm().
eps.Pvalue: \(p\)-values below this level will be printed as "<eps.Pvalue".
print.formula, print.fitinfo, print.coefmat, print.message, print.deviances, print.drop, print.offset, print.call: which components of the fit summary to print.

Details

summary.ergm() tries to be smart about formatting the coefficients, standard errors, etc.

The default printout of the summary object contains the call, number of iterations used, null and residual deviances, and the values of AIC and BIC (and their MCMC standard errors, if applicable). The coefficient table contains the following columns:

Estimate, Std. Error - parameter estimates and their standard errors
MCMC % - if total.variation=TRUE (default) the percentage of standard error attributable to MCMC estimation process rounded to an integer. See also vcov.ergm() and its sources argument.
z value, Pr(>|z|) - z-test and p-values

Examples

Run this code


 data(florentine)

 x <- ergm(flomarriage ~ density)
 summary(x)