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NEWS file for the ergm.ego package
Changes in version 1.1.3
NEW FEATURES
-
triangles()EgoStat has been added.
BUG FIXES
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The package now works under ergm 4.9.0.
OTHER USER-VISIBLE CHANGES
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EgoStat
esp, and functionas.egor.network()now run much faster.
Changes in version 1.1.2
BUG FIXES
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Changes in term naming for the
degreeterm for consistency with ergm 4.8. -
mixingmatrix()method foregorobjects now behaves more consistently with the method in network. -
Categorical
EgoStats now base their levels selection on egos only; this means that selectorsLARGESTandSMALLESTnow work consistently with ergm. If the alters have levels that egos do not, a warning is issued.
Changes in version 1.1.1
NEW FEATURES
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An
EgoStatforabsdiffcat()has been added.
BUG FIXES
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degreedist()has been fixed.
OTHER USER-VISIBLE CHANGES
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logLik()method forergm.egoobjects has been added; it produces an informative error message. -
Documentation fixes.
Changes in version 1.1.0
NEW FEATURES
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ergm.ego()now has abasis=argument. So doessimulate.ergm.ego(), for consistency (as an alias for thepopsize=argument). -
simulate.ergm.ego()'spopsize=argument can now be a network object, enabling simulation from any starting network.
BUG FIXES
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gof.ergm.ego(GOF="degree")now handles the case in which the observed or simulated degree distribution is dense and the LHS network is small more gracefully.gof.ergm.ego()was scrambling the the order of ESP terms.simulate.ergm.ego()is now more robust to models with offsets and extreme “dropped” statistics.ergm.ego()(viacontrol.ergm.ego(ppopsize=)) andsimulate.ergm.ego(popsize=)can once again takedata.frames andtibbles to specify the pseudopopulation network composition directly.
OTHER USER-VISIBLE CHANGES
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simulate.ergm.ego()now preserves some of the attributes attached bysimulate.ergm()to the statistics matrix, including"monitored". -
simulate.ergm.ego()no longer supportsergm.egoobjects fit under under ergm < 4.
Changes in version 1.0.1
BUG FIXES
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Documentation fixes, particularly for compatibility with ergm 4.2.
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Summary for
ergm.egofits now displays the original call rather than the instrumentalergm()call.
OTHER USER-VISIBLE CHANGES
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control.ergm.ego()praameterignore.max.alters=now defaults toTRUE, since simulation studies (Krivitsky, et al. 2020) showed that they did more harm than good.
Changes in version 1.0.0
NEW FEATURES
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This package now uses the egor package's
egorclass for data storage and manipulation. A converteras.egor.egodata()is provided. -
ergm.ego()now supports complex survey designs set onegorobjects. -
ergm.ego()and the summary methods can now fit triadic effects (gwesp,esp,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
gwdegree -
A number of improvements to the goodness-of-fit routines.
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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.
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For nonscaling statistics such as
meandeg, standard errors can now be computed. -
Network size adjustment can now be disabled during fitting.
BUG FIXES
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Various fixes to
degreedist(),mixingmatrix(), and other methods.
OTHER USER-VISIBLE CHANGES
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The function that was previously
as.network.egodata()for constructing an empty network having the same composition as the egocentric dataset has been superseded bytemplate_network(). -
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 atable.
Changes in version 0.6.0
NEW FEATURES
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predict.ergm.ego, apredictmethod forergm.egohas been implemented. (Thanks, MichaĆ Bojanowski.) -
Nonscaling statistic
meandeghas been added.
OTHER USER-VISIBLE CHANGES
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EgoStat.*functions no longer need to be exported, reducing namespace pollution.
BUG FIXES
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ergm.egonow detects when a coefficient has been dropped byergmdue to the statistic having an extreme value and subsets the variance matrices accordingly. -
control.ergm.egonow callsmatch.argonppopsizeonly ifppopsizeis of classcharacter. This allowsppopsizeto be of classnetworkwhen callingcontrol.ergm.ego. -
A more thorough search mechanism for
EgoStat.*functions no longer requires them to be exported.
Changes in version 0.5.0
NEW FEATURES
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ergm's new nodal attributes user interface has been extended toergm.ego. -
mixingmatrix.egodataanddegreedist.egodatanow have an option to ignore sampling weights. -
Simulation frmo an
ergm.egofit now inherints the constraints. -
It is now possible to specify the (pseudo)population network temlate directly by passing it to
control$ppopsize. -
It is now possible to infer main effects (
nodefactorandnodecov) when the attribute has only been obseved on the egos.
BUG FIXES
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A wide variety of minor bugs has been fixed. See commit log and issue tracker for details.
OTHER USER-VISIBLE CHANGES
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A number of robustifications have been made.
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ergm.egonow produces sensible error messages when terms have alter categories that egos do not. -
Chad Klumb has been added as a contributor.
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gof.ergm.ego's default MCMC.interval is now the MCMC.interval of the ergm fit scaled by the ratio between the fit'sMCMC.samplesizeand GoF control'snsim. -
gof.ergm.egonow 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.
Changes in version 0.4.0
NEW FEATURES
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mmterm has been implemented.degreedistnow has an option to not plot, and returns the calculated degree distribution (invisibly, if plotting). -
offsetterms are now handled. More
EgoStatnow handle more options that theirergmcounterparts do.-
ergm.ego'sppopsizecontrol parameter andsimulatemethod forergm.ego'spopsizeargument now take a data frame of egos to use as the pseudopopulation.
BUG FIXES
Package now works with
ergm3.9.-
degreedistnow handles sampling weights correctly, and has been fixed in other ways. Bootstrap and jackknife now handle one-dimentional stats correctly.
-
mixingmatrix.egodatanow handles ego ID column names other thanvertex.names. Thanks to Deven Hamilton for reporting this bug. Non-numeric ego IDs are also handled correctly. -
mixingmatrix.egodatano longer rounds the row probabilities before returning when calledrowprob=TRUE.
OTHER USER-VISIBLE CHANGES
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degreedist.egodatais now anegodatamethod ofdegreedist.
Changes in version 0.3.0
NEW FEATURES
This is the initial public release.