manynet
.Makevars.in
file that produced a note when check as CRAN. checkEvents()
method addresses S3 generic/method consistency.GatherPreprocessing()
.estimate()
.estimate()
for DyNAM
models.estimate()
when using
a parameter is fixed to a value. startTime
and endTime
bug on DyNAM
and REM
models
preprocessing.GatherPreprocessing()
. Experimental functionality.aes_string()
deprecation.C++
engine on DyNAM-rate..GlobalEnv
and drop goldfishObjects()
.vcov()
, now is possible to use stats::confint()
to obtain
confidence interval for parameters estimates under asymptotic normality, and
also get them from a tidy()
call.silent
parameter replace by progress
.
progress
and verbose
can be set with global options with the same name.logLik()
, now is possible to use AIC()
and BIC()
from stats
package and make likelihood ratio test of nested models using
lmtest::lrtest()
.define
functions, linkEvents()
and print
methods.
The reserved names and expected variables are explained.fig.retina
from figures in vignettes and keeps default size.vignette("goldfishEffects")
documentation for closure effects.C
engine.opportunityList
egoAlterInt(list(egoAttr, alterAttr))
migraph
packageR
clSender(net) -> commonSender(net)
clReceiver(net) -> commonReceiver(net)
mixedClSender(list(net1, net2)) -> mixedCommonSender(list(net1, net2))
mixedClReceiver(list(net1, net2)) -> mixedCommonReceiver(list(net1, net2))
examine.outliers()
and examine.changepoints()
to plot more informative plots (with {ggplot2}
)teaching2.Rmd
that also indicates these extensionsteaching1.Rmd
with the "How to start"{broom}
-related functions tidy()
and glance()
examine.outliers()
and examine.changepoints()
to plot more informative plots (with {ggplot2}
)teaching2.Rmd
that also indicates these extensionsteaching1.Rmd
with the "How to start"R
defineGroups_interaction(interactions_data, actors, seed.randomization)
* Estimation functions for the joining and leaving rates of a DyNAM-i model
R
estimate(
dependent.events_interactions ~ 1 + intercept(network_interactions, joining = 1) +
ego(actors$age,joining = 1, subType = "centered") +
ego(actors$age,joining = -1, subType = "centered"),
model = "DyNAMi", subModel = "rate")
R
estimate(
dependent.events_interactions ~ diff(actors$age,subType="averaged_sum") ,
model = "DyNAMi", subModel = "choice",
estimationInit = list(opportunitiesList = opportunities))
* New closure effects for model = "DyNAM"
with subModel = "choice"
and model = "REM"
.
Documentation is updated accordingly.
R
cycle(bilatnet)
clSender(bilatnet)
clReceiver(bilatnet)
mixedCycle(list(bilatnet, contignet))
mixedClSender(list(bilatnet, contignet))
mixedClReceiver(list(bilatnet, contignet))
print-method
and update-method
.tertius_diff()
and node_trans()
are changed to tertiusDiff()
and
nodeTrans()
complaining with naming convention.mixedTrans()
effect is created. It requires the definition of two networks
to compute the number of two paths between nodes.R
mixedTrans(list(bilatnet, contignet))
estimate()
no longer give warnings in R 4.0.0.linkEvents()
is refactored as a S3 method.print
or summary
methods for goldfish
objects are developed.head()
and tail()
methods for nodes.goldfish
, network.goldfish
and dependent.goldfish
are available.tertius()
and tertius_diff()
effects are created. It requires the
definition of a network and an attribute.R
tertius_diff(bilatnet, states$gdp)
tertius(bilatnet, states$gdp)
estimate()
now estimation routine in C
for model = "DyNAM"
and
subModel = "choice_coordination"
.estimate()
parameter engine
through estimationInit
argument control the estimation
routine used.R
mod01 <- estimate(callsDependent ~ inertia + recip + trans,
model = "DyNAM", subModel = "choice",
estimationInit = list(engine = "gather_compute"))
estimate()
now estimation routine in C
except for model = "DyNAM"
and
subModel = "choice_coordination"
.model = "DyNAM"
and subModel = "rate"
.inertia
fixed bug when weighted = TRUE
.modelType
argument in estimate()
have been deprecated in favor of model
and submodel
.estimate()
.defineDependentEvents()
, defineGlobalAttribute()
,
defineNetwork()
, defineNodes()
and linkEvents()
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