NEWS file for the ergm.ego package

Changes in version 1.1.4

NEW FEATURES

• Some of the slower routines now print progress reports via cli.

BUG FIXES

• The package now works under ergm 4.12.0.

OTHER USER-VISIBLE CHANGES

• Standard error calculation has been made slightly more robust.

• Some bibliographic references in the documentation have been updated.

Changes in version 1.1.3

NEW FEATURES

• triangles() EgoStat has been added.

BUG FIXES

• The package now works under ergm 4.9.0.

OTHER USER-VISIBLE CHANGES

• EgoStat esp, and function as.egor.network() now run much faster.

Changes in version 1.1.2

BUG FIXES

• Changes in term naming for the degree term for consistency with ergm 4.8.

• mixingmatrix() method for egor objects now behaves more consistently with the method in network.

• Categorical EgoStats now base their levels selection on egos only; this means that selectors LARGEST and SMALLEST now 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

• An EgoStat for absdiffcat() has been added.

BUG FIXES

• degreedist() has been fixed.

OTHER USER-VISIBLE CHANGES

• logLik() method for ergm.ego objects has been added; it produces an informative error message.

• Documentation fixes.

Changes in version 1.1.0

NEW FEATURES

• ergm.ego() now has a basis= argument. So does simulate.ergm.ego(), for consistency (as an alias for the popsize= argument).

• simulate.ergm.ego()'s popsize= argument can now be a network object, enabling simulation from any starting network.

BUG FIXES

• 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() (via control.ergm.ego(ppopsize=)) and simulate.ergm.ego(popsize=) can once again take data.frames and tibbles to specify the pseudopopulation network composition directly.

OTHER USER-VISIBLE CHANGES

• simulate.ergm.ego() now preserves some of the attributes attached by simulate.ergm() to the statistics matrix, including "monitored".

• simulate.ergm.ego() no longer supports ergm.ego objects fit under under ergm < 4.

Changes in version 1.0.1

BUG FIXES

• Documentation fixes, particularly for compatibility with ergm 4.2.

• Summary for ergm.ego fits now displays the original call rather than the instrumental ergm() call.

OTHER USER-VISIBLE CHANGES

• control.ergm.ego() praameter ignore.max.alters= now defaults to TRUE, since simulation studies (Krivitsky, et al. 2020) showed that they did more harm than good.

Changes in version 1.0.0

NEW FEATURES

• 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 egor objects.

• 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.

• 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.

BUG FIXES

• Various fixes to degreedist(), mixingmatrix(), and other methods.

OTHER USER-VISIBLE CHANGES

• 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 template_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 a table.

Changes in version 0.6.0

NEW FEATURES

• predict.ergm.ego, a predict method for ergm.ego has been implemented. (Thanks, Michał Bojanowski.)

• Nonscaling statistic meandeg has been added.

OTHER USER-VISIBLE CHANGES

• EgoStat.* functions no longer need to be exported, reducing namespace pollution.

BUG FIXES

• ergm.ego now detects when a coefficient has been dropped by ergm due to the statistic having an extreme value and subsets the variance matrices accordingly.

• control.ergm.ego now calls match.arg on ppopsize only if ppopsize is of class character. This allows ppopsize to be of class network when calling control.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

• ergm's new nodal attributes user interface has been extended to ergm.ego.

• mixingmatrix.egodata and 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 control$ppopsize.

• It is now possible to infer main effects (nodefactor and nodecov) when the attribute has only been obseved on the egos.

BUG FIXES

• A wide variety of minor bugs has been fixed. See commit log and issue tracker for details.

OTHER USER-VISIBLE CHANGES

• 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 nsim.

• 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.

Changes in version 0.4.0

NEW FEATURES

• 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.

• More EgoStat now handle more options that their ergm counterparts do.

• ergm.ego's ppopsize control parameter and simulate method for ergm.ego's popsize argument now take a data frame of egos to use as the pseudopopulation.

BUG FIXES

• Package now works with ergm 3.9.

• 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 other than 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 rowprob=TRUE.

OTHER USER-VISIBLE CHANGES

• degreedist.egodata is now an egodata method of degreedist.

Changes in version 0.3.0

NEW FEATURES

• This is the initial public release.