set.seed(); rpanet()
due to potential
cross-platform inconsistencies.directed
in rpanet()
into initial.network
;
rpanet(nstep = 1e4, initial.network = list(directed = TRUE))
.isolates
in clustcoef()
to accept binary input.distribution
, dparams
and shift
arguments from both
rpa_control_newedge()
and rpa_control_edgeweight()
; the new argument
sampler
accepts a function used for sampling the number of new edges and
edge weights.print.rpacontrol()
and summary.wdnet()
.binary
method due
to negligible performance gain.wdnet
objects.wdnet
and rpacontrol
objects.Updated function rpanet
.
seednetwork
to initial.network
and changed seednetwork = NULL
to initial.network = list(edgelist = matrix(c(1, 2), nrow = 1))
;control = NULL
to control = list()
;naive
to linear
; nodelist
to bag
; edgesampler
to bagx
;Sort nodes from the seed network according to their preference scores before the sampling process.
Renamed rpanet
control functions: rpactl.foo()
to rpa_control_foo()
.
Renamed cvxr.control()
to cvxr_control()
.
dprewire
and dprewire.range
.
eta
and corresponding assortativity levels.CVXR
.rpactl.preference
.rpanet
with binary
approach: renamed node structures (fix LTO issues).