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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.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
;rpanet
control functions:
rpactl.foo()
to rpa_control_foo()
.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).These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.