Documentation fixes, particularly for compatibility with ergm 4.2.
ergm.ego fits now displays the original call rather than the instrumental
ignore.max.alters= now defaults to
TRUE, since simulation studies (Krivitsky, et al. 2020) showed that they did more harm than good.
This package now uses the egor package's
egor class for data storage and manipulation. A converter
as.egor.egodata() is provided.
ergm.ego() now supports complex survey designs set on
ergm.ego() and the summary methods can now fit triadic effects (
transitiveties) when alter-alter ties are available.
ergm.ego() can now handle missing alter attributes in some circumstances, and provided they are missing completely at random.
A number of new egostats have been implemented, including
A number of improvements to the goodness-of-fit routines.
snctrl() UI for specifying control parameters is supported.
Curved ERGMs are now supported; this capability should be considered experimental, as uncertainty estimates have not been rigorously derived.
For nonscaling statistics such as
meandeg, standard errors can now be computed.
Network size adjustment can now be disabled during fitting.
Various fixes to
mixingmatrix(), and other methods.
The function that was previously
as.network.egodata() for constructing an empty network having the same composition as the egocentric dataset has been superseded by
Manually specified pseudo-population is handled better.
degreedist() method for egocentric data now defauts to not making plots.
mixingmatrix() method for egocentric data now returns a
predict method for
ergm.ego has been implemented. (Thanks, Michał Bojanowski.)
meandeg has been added.
EgoStat.* functions no longer need to be exported, reducing namespace pollution.
ergm.ego now detects when a coefficient has been
ergm due to the statistic having
an extreme value and subsets the variance matrices accordingly.
control.ergm.ego now calls
ppopsize only if
ppopsize is of class
character. This allows
ppopsize to be of class
network when calling
A more thorough search mechanism for
EgoStat.* functions no longer requires them to be exported.
ergm's new nodal attributes user interface has been extended to
degreedist.egodata now have an option to ignore sampling weights.
Simulation frmo an
ergm.ego fit now inherints the constraints.
It is now possible to specify the (pseudo)population network temlate directly by passing it to
It is now possible to infer main effects (
nodecov) when the attribute has only been obseved on the egos.
A wide variety of minor bugs has been fixed. See commit log and issue tracker for details.
A number of robustifications have been made.
ergm.ego now produces sensible error messages when terms have alter categories that egos do not.
Chad Klumb has been added as a contributor.
gof.ergm.ego's default MCMC.interval is now the MCMC.interval of the ergm fit scaled by the ratio between the fit's
MCMC.samplesize and GoF control's
gof.ergm.ego now only calculates GOF for degree values up to twice the highest observed in the data or 6, whichever is higher with an additional category to catch the higher values.
mm term has been implemented.
degreedist now has an option to
not plot, and returns the calculated degree distribution
(invisibly, if plotting).
offset terms are now handled.
EgoStat now handle more options that their
ergm counterparts do.
ppopsize control parameter and
simulate method for
argument now take a data frame of egos to use as the
Package now works with
degreedist now handles
sampling weights correctly, and has been fixed in other ways.
Bootstrap and jackknife now handle one-dimentional stats correctly.
mixingmatrix.egodata now handles ego ID column names
vertex.names. Thanks to Deven Hamilton for
reporting this bug. Non-numeric ego IDs are also handled correctly.
mixingmatrix.egodata no longer rounds the row
probabilities before returning when called
degreedist.egodata is now an
egodata method of
This is the initial public release.