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ergm (version 3.0-3)

stergm: Separable Temporal Exponential Family Random Graph Models

Description

stergm is used for finding Separable Temporal ERGMs' (STERGMs) Conditional MLE (CMLE) (Krivitsky and Handcock, 2010) and Equilibrium Generalized Method of Moments Estimator (EGMME) (Krivitsky, 2009).

Usage

stergm (nw, 
          formation, 
          dissolution, 
          estimate, 
          times=NULL, 
          offset.coef.form=NULL, 
          offset.coef.diss=NULL,
          targets=NULL, 
          target.stats=NULL,
          eval.loglik=FALSE,
          control=control.stergm(),
          verbose=FALSE, 
          ...)

Arguments

nw
A network object (for EGMME); or networkDynamic object, a network.list
formation, dissolution
One-sided ergm-style formulas for the formation and dissolution models, respectively.
estimate
One of "EGMME" for Equilibrium Generalized Method of Moments Estimation, based on a single network with some temporal information and making an assumption that it is a product of a STERGM process running to its stationary (equilibrium) distrib
times
For CMLE and CMPLE estimation, times or indexes at which the networks whose transition is to be modeled are observed. Default to c(0,1) if nw is a networkDyna
offset.coef.form
Numeric vector to specify offset formation parameters.
offset.coef.diss
Numeric vector to specify offset dissolution parameters.
targets
One-sided ergm-style formula specifying statistics whose moments are used for the EGMME. Unused for CMLE and CMPLE.
target.stats
A vector specifying the values of the targets statistics that EGMME will try to match. Defaults to the statistics of nw. Unused for CMLE and CMPLE.
eval.loglik
Whether or not to calculate the log-likelihood of a CMLE STERGM fit. See ergm for details.
control
A list of control parameters for algorithm tuning. Constructed using control.stergm.
verbose
logical or integer; if TRUE or positive, the program will print out progress information. Higher values result in more output.
...
Additional arguments, to be passed to lower-level functions.

Value

  • stergm returns an object of class stergm that is a list consisting of the following elements:
  • formation, dissolutionFormation and dissolution formulas, respectively.
  • targetsThe targets formula.
  • target.statsThe target statistics.
  • estimateThe type of estimate.
  • opt.historyA matrix containing the full trace of the EGMME optimization process: coefficients tried and target statistics simulated.
  • sampleAn mcmc object containing target statistics sampled at the estimate.
  • covarThe full estimated variance-covariance matrix of the parameter estimates for EGMME. (Note that although the CMLE formation parameter estimates are independent of the dissolution parameter estimates due to the separability assumption, this is not necessarily the case for EGMME.)
  • formation.fit, dissolution.fitFor CMLE and CMPLE, ergm objects from fitting formation and dissolution, respectively. For EGMME, stripped down ergm-like lists.
  • networkThe original network.
  • controlThe control parameters used to fit the model.
  • See the method print.stergm for details on how an stergm object is printed. Note that the method summary.stergm returns a summary of the relevant parts of the stergm object in concise summary format.

Model Terms

See ergm and ergm-terms for details. At this time, only linear ERGM terms are allowed.

References

Krivitsky PN (2009). Statistical Models for Social Network Data and Processes. PhD Thesis. University of Washington.

Krivitsky PN, Handcock MS (2010). A Separable Model for Dynamic Networks. http://arxiv.org/abs/1011.1937

See Also

network, %v%, %n%, ergm-terms