NEWS | R Documentation |
tergm
package Some Metropolis-Hastings proposal functions would sometimes
return incorrect acceptance probabilities when combined with the
bd
constraint. This has been
fixed.
In simulate.networkDynamic
, an error in which
vertices were queried and updated in the simulation has been
fixed.
simulate.networkDynamic
and
simulate.network
functions now take an additional
argument, time.offset
. See help for those functions for
details.
The Tie-NonTie (TNT) proposal has been implemented for dissolution phase models. This should improve mixing and inference for these models.
stergm
and simulate.stergm
now determine the
number of Metropolis-Hastings steps per time step adaptively,
stopping when the formation/dissolution process appears to have
converged.
The previously deprecated start and end attr values attached
to networks returned by simulate.network
and
simulate.networkDynamic
have been removed and
replaced with observation spells recorded as a
net.obs.period
network attribute.
MCMC.burnin
and MCMC.interval
arguments to
control.stergm
, control.simulate.network
, and
control.simulate.stergm
have been replaced by a different
mechanism. See the help for the respective control functions for
more information.
No longer generates deprecation warnings about start and end
attrs when various internal functions use as.data.frame. Resolved
by replacing start and end with a net.obs.period
object.
A bug in the check for whether terms were amenable to being fit using STERGM CMLE for multiple transitions has been fixed.
Some minor documentation typos have been fixed.
Version 3.1.1 has been skipped to ease upgrading for those using a preview release.
This package consists of the dynamic network modeling code that has been
split out of the ergm
package.
Changes listed in the following sections are relative to
ergm
version 3.0.
Although fitting the EGMME for dissolution was possible
before, it was impractical due to nonidentifiability: for example,
one cannot fit both edges
formation and
edges
dissolution with only one edges
target statistic. Four new statistics have been added and
documented that focus on targeting observed and hazard:
mean.age
, edgecov.mean.age
,
degree.mean.age
, degrange.mean.age
,
edge.ages
, edgecov.ages
, and
edges.ageinterval
. This allow jointly fitting
formation and dissolution.
In addition to the progress plot, EGMME fitting routines can now plot the estimated gradient matrix and the matrix of correlations among the target statistics.
EGMME fitting is now more adaptive when determining when to stop the optimization and return the result.
EGMME fitting can now take advantage of multiple CPUs, cores, or cluster nodes for faster and more robust fitting.
EGMME and CMLE fitting can now accommodate a
constraints
argument. However, note that the constraints
apply to post-formation (y^+=y^0\cup\y^1) and
post-dissolution (y^-=y^0\cap\y^1) networks, not to the
final network (y^1). This may change in the future.
CMLE can now be fit to more than two networks. (Not all ERGM terms and constraints can be used in this mode, however.)
A new (sort of) function, tergm.godfather
has
been fixed and documented; it can be used to apply a specific set
of changes to a network, returning statistics of interest as it
evolves. In particular, it can be used to “retrace” the evolution
of a networkDynamic
, calculating statistics at
discrete time points along the way.
tergm
now implements a
formula-based summary
method for networkDynamic
LHS, to compute dynamic
network statistics at specified time points.
Fitting CMLE to network series with transitioned-from
networks having missing dyads is now possible, using automatic
imputation. See impute.network.list
and
control.tergm
.
STERGM simulate
can now be used
for CMLE fits, takes a number of new arguments, and can be used to
“resume” a simulation from a networkDynamic
object.
gof
methods have been implemented for CMLE fits.
stergm
EGMME initial fitting code has been
vastly improved.
The EGMME fitting algorithm has been vastly improved and is now a lot more adaptive and able to recover from problems. Many bugs have also been fixed.
A number of control.stergm
parameters had been
renamed and otherwise chaged.
Argument statsonly
to the
simulate.stergm
and related functions has been
deprecated in favor of output
.
The conditional MPLE (CMPLE) for formation and dissolution is now fit correctly. This also means that the starting values for the CMLE are much better.
Bugs in EGMME code related to handling of bipartite networks have been fixed.