NEWS | R Documentation |
ergm
packageergmMPLE
can now output an array of change
scores associated with each dyad. See the help page for more
details.
Some Metropolis-Hastings proposal functions would sometimes
return incorrect acceptance probabilities when combined with the
bd
constraint. This has been
fixed.
In simulate.ergm
and
simulate.formula
, some combinations of
control$parallel
, statsonly
, and sequential
arguments would cause an error. This has been fixed. Note that the
current implementation of parallel simulation when
statsonly=FALSE
or sequential=FALSE
is very
inefficient.
A namespace bug in the likelihod calculation code, reported by Matthew Hoover, has been fixed.
MPLE for some degree-based constrained has been reenabled.
Argument fitmodel
to ergmMPLE
has been
deprecated in favor of output
.
Default SAN.burnin
control parameter has been
increated to 100,000.
Long-standing bugs in MCMC standard error calculation have been fixed. In particular, MCMC standard errors are now calculated for offset models, and they are no longer overestimated (by too much).
san
now behaves sensibly when the network exceeds the
number of edges allocated.
degrange
terms now initialize correctly for their
respective network types.
Some spurious warnings are no longer printed.
A variety of minor errors has been fixed.
ergm
's implementation and tests now work with
network
version 1.8. (In
particular, bipartite=0
is now treated as a network with no
actors.)
Infrastructure
has been added for fitting valued ERGMs of Krivitsky (2012). The
“user interface” is subject to change, however. (The
implementation of reference measures for counts can be found in R package
ergm.count
)
ergm
itself now includes
rudimentary implementations for discrtete uniform and continuous
uniform reference measures. See help('ergm-references')
.
A large number of ERGM terms for counts have been
implemented and documented. See help('ergm-terms')
.
A number of new binary ERGM terms have been
implemented as well. Particularly, degrange
,
odegrange
, idegrange
,
b1degrange
, and b2degrange
, which
generalize degree
and concurrent
by
allowing the user to specify contiguous ranges of degree values.
A rudimentary “degeneracy” heuristic has been
implemented and enabled by default, immediately stopping MC MLE
optimization if simulating from a parameter configuration of
interest encounters produces networks with too many edges. See
MCMLE.density.guard
argument in control.ergm
documentation for details. Note that this is intended mainly to
keep the fitting from bogging down on bad models, and it should
not be used as a formal degeneracy diagnostic.
ergm
now keeps track of of when
it is and when it's not possible to evaluate the likelihood of the
null model (a model with no terms), and takes into account whether
a model is constrained, has missing dyads, etc.. This can also
improve the MPLE.
A new generic, logLikNull
has been added that
returns the null model likelihood.
For models where this is not possible, the null likelihood (and deviance, etc.) is defined to be 0.
A new constraint, blockdiag
has been added, for
modeling networks with only within-block ties allowed. This is
useful for, e.g., fitting an ERGM to several networks jointly. See
? 'ergm-constraints'
for available constraints.
The implementation of dynamic network models has been moved to a
new package, tergm
.
Sample space constraints degrees
,
idegrees
, odegrees
,
b1degrees
, b2degrees
have
been reimplemented or fixed.
Certain functions are now only exported if they haven't
already be defined (e.g., by
latentnet
).
Documentation and citation information have been cleaned up
and reorganized. In particular, see ? 'ergm-constraints'
,
? 'ergm-terms'
for an article on terms, and ?
'ergm-references'
for reference measures implemented.
ergm
now exports header and
stub files for the LinkingTo:
API, and package
ergm.userterms
now uses it. Please see
inst/include/README
before using it, however.
Dynamic network modeling code has been moved to
tergm
package.
Function statnet.edit
has been removed.
Some bugs introduced by the developers relying on a certain
behavior of the .C
API which had changed have been
fixed.
Some undocumented terms have been fixed and documented,
including odegreepopularity
,
idegreepopularity
, degreepopularity
,
and smalldiff
.
Facilities for fitting and simulating Separable Temporal
ERGMs (STERGMs) of Krivitsky (2009) and, Krivitsky and Handcock
(2010) have been added. See stergm
and
simulate
.
ergm
MCMLE will now test if the optimization
has converged to the MLE and stop if it detects convergence.
ergm
Now checks if a constraint specified in
the constraints
argument fixes any statistics in the
model (e.g., ergm(y~edges, constraints=~edges)
). It issues a
warning, and fixes their parameters at 0.
simulate
functions now take an argument
monitor
, a one-sided formula for additional statistics to
be returned. This allows one to easily simulate from an
ergm
or stergm
fit statistics that
were not in the fitted model.
ergm
can now optionally detect when a burn-in
is insufficient and retry it until it is sufficient. See
control.ergm
argument MCMC.burnin.retries
for
details.
ergm
MCMLE now stores “history” of
θ and simulated statistics.
ergm
extreme statistics detection (if
control.ergm(drop=TRUE)
) can now detect both extremely high
and extremely low values, setting the coefficients to +Inf and
-Inf respectively. Direction of “dropping” is returned.
An initial method "zeros"
has been, to use a vector
of zeros as starting parameters.
A number of new ERGM terms have been added.
ergm
, simulate
,
and other functions now enforce a conceptual separation between
what to fit, which is controlled by arguments to the
function and how to fit it, which is controlled by the
control
lists, generated by control.ergm
and
control.simulate
, respectively. (Old arguments for
ergm
and simulate
still work with a warning, and
they may be removed later.)
The data structure returned by
simulate
is now a list of networks
with attr
-style attributes describing how it was
generated. The list has print and summary methods, and it can be
used in the left-hand side of a
summary
formula.
Matrices of sample statistics returned by ergm
are mcmc
objects (or
mcmc.list
objects, for parallel computing).
Arguments theta
have been renamed to
coef
. Arguments meanstats
have been renamed to
target.stats
. Many control parameters have also been
renamed and reorganized. (Old parameters still work with a
warning, and they may be removed later.)
A number of arguments to control.ergm
,
control.simulate
, and others, have been renamed.
ergm
now uses bridge sampling evaluate the
log-likelihood by default. (Before, the default was to not
evaluate it.)
mcmc.diagnostics
has been
rewritten:
Raftery-Lewis diagnostic has been replaced with several others, including tests of (non)convergence.
For fits with missing data, diagnostics for both the constrained and the unconstrained sample are printed and plotted.
Plots now use lattice
graphics, if available.
Handling of networks with many edges has been improved somewhat.
gof.ergm
and gof.formula
now set
the statistics used to diagnose the fit adaptively, depending on
the directedness of the network being modeled.
The following control parameters have been removed or
renamed:
maxedges
, prop.weights
, prop.args
,
packagename
, summarizestats
, nr.maxit
,
nr.reltol
, maxNumDyadTypes
,
steplength
, initialfit
, style
,
obs.MCMCsamplesize
, obs.interval
, obs.burnin
,
compress
, metric
, force.mcmc
,
adaptive.trustregion
, adaptive.epsilon
,
mcmc.precision
, method
, MPLEtype
,
check.degeneracy
, maxMPLEsamplesize
,
MPLEsamplesize
, phase1_n
, nsubphases
,
RobMon.phase1n_base
, RobMon.phase2n_base
,
RobMon.phase2sub
, RobMon.init_gain
,
RobMon.phase3n
, trustregion
, stepMCMCsize
,
steppingmaxit
, gridsize
, sequential
,
returnMCMCstats
, calc.mcmc.se
, hessian
,
prop.weights
, prop.args
, and packagenames
.
The following arguments to functions have been moved to the
corresponding control functions, removed or renamed:
burnin
, MCMCsamplesize
, interval
,
maxit
, seed
, and theta0
.
Fixed some errors in log-likelihood calculation, especially in models with missing data and/or offset terms.
Parallel processing has been made more robust. In
particular, ergm
now checks to make
sure that the version it finds on slave nodes is the same as the
version on the master. Also, although ergm
will
start its own cluster as needed, it will also detect if an MPI
cluster has already been started and use that.
Several bugs relating to handling models with with offset terms have been fixed.
The bounded degree (bd
) ERGM would sometimes tabulate
degrees incorrectly. This has been fixed.
Miscellaneous robustification and bug fixes.
The “news” feature has been implemented. Type
news(package="ergm")
to see the version's updates.
A function ergm.allstats
was added to
calculate all possible network statistics for a given ERGM and
network. The number of possible networks grows on the order of 2^{n^2}, so this should only be used for small networks. Related function ergm.exact
calculates exact log-likelihood for a particular canonical parameter and a particular ergm.
A cutoff
argument has been added to specify maximum shared partner
count or degree to be evaluated to the following model terms:
gwb1degree
, gwb2degree
, gwdegree
, gwdsp
, gwesp
, gwidegree
, gwnsp
,
gwodegree
. This significantly speeds up fitting
curved ERGMs on large, sparse networks.
The logLik
method for
ergm
objects, with the attendant AIC
and BIC
methods, has been implemented.
Calculation of loglikelihoods for MCMC-based ergm fits has
been reengineered to use bridge sampling for dyad-dependent
models. (See logLik.ergm
,
ergm.bridge.llr
, and
ergm.bridge.dindstart.llk
.)
A generic function is.dyad.independent
to test
whether an ERGM fit or formula is dyad-independent has been added.
A generic function fix.curved
to convert
curved exponential family models to variants in which the curved
parameters are fixed has been added. See the function
documentation for usage scenarios.
A generic function enformulate
function to
work around a current limitation in the ergm
function to substitute curved parameters from a model fit into the
model formula, allowing them to be used as initial values (the
theta0
argument). See the function documentation for usage
scenarios.
The following new models terms have been added:
degcrossprod
and degcor
.
Tests for change statistics have been added.
A new dataset has been added: kapferer
, the well-known
tailor shop network dataset of Kapferer (1972).
The package has been “standardized” to represent
directed ties as (tail,head)
.
Log-likelihood calculation for dyad-dependent models has been fixed.
Some errors in estimating parameters in curved exponential family models have been fixed.
gof
now automatically selects the
right goodness-of-fit statistics for the network type (directed
vs. undirected) given.
Bug in is.inCH in 2.4-2 fixed in 2.4-3.
as.directed
function has been removed.
All model terms included in the package have been
reimplemented using the new InitErgmTerm
framework.