A logLik method for ergm fits.
A function to return the log-likelihood associated with an
ergm
fit, evaluating it if
necessary. If the log-likelihood was not computed for
object
, produces an error unless eval.loglik=TRUE
.
## S3 method for class 'ergm' logLik( object, add = FALSE, force.reeval = FALSE, eval.loglik = add || force.reeval, control = control.logLik.ergm(), ... )
object |
|
add |
Logical: If |
force.reeval |
Logical: If |
eval.loglik |
Logical: If |
control |
A list of control parameters for algorithm tuning.
Constructed using |
... |
Other arguments to the likelihood functions. |
As of version 3.1, all likelihoods for which logLikNull
is
not implemented are computed relative to the reference
measure. (I.e., a null model, with no terms, is defined to have
likelihood of 0, and all other models are defined relative to
that.)
Hunter, D. R. and Handcock, M. S. (2006) Inference in curved exponential family models for networks, Journal of Computational and Graphical Statistics.
# See help(ergm) for a description of this model. The likelihood will # not be evaluated. data(florentine) ## Not run: # The default maximum number of iterations is currently 20. We'll only # use 2 here for speed's sake. gest <- ergm(flomarriage ~ kstar(1:2) + absdiff("wealth") + triangle, eval.loglik=FALSE) gest <- ergm(flomarriage ~ kstar(1:2) + absdiff("wealth") + triangle, eval.loglik=FALSE, control=control.ergm(MCMLE.maxit=2)) # Log-likelihood is not evaluated, so no deviance, AIC, or BIC: summary(gest) # Evaluate the log-likelihood and attach it to the object. # The default number of bridges is currently 20. We'll only use 3 here # for speed's sake. gest.logLik <- logLik(gest, add=TRUE) gest.logLik <- logLik(gest, add=TRUE, control=control.logLik.ergm(nsteps=3)) # Deviances, AIC, and BIC are now shown: summary(gest.logLik) # Null model likelihood can also be evaluated, but not for all constraints: logLikNull(gest) # == network.dyadcount(flomarriage)*log(1/2) ## End(Not run)
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