summary.ergm: Summarizing ERGM Model Fits

In ergm: Fit, Simulate and Diagnose Exponential-Family Models for Networks

Summarizing ERGM Model Fits

Description

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

Usage

## S3 method for class 'ergm'
summary(
  object,
  ...,
  correlation = FALSE,
  covariance = FALSE,
  total.variation = TRUE
)

## S3 method for class '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,
  ...
)

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

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()

See Also

The model fitting function ergm(), print.ergm(), and base::summary(). Function stats::coef() will extract the matrix of coefficients with standard errors, t-statistics and p-values.

Examples

 data(florentine)

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

ergm documentation built on Oct. 7, 2024, 5:08 p.m.