consensus_tree
creates a consensus tree from several fitted
hierarchical random graph models, using phylogeny methods. If the hrg
argument is given and start
is set to TRUE
, then it starts
sampling from the given HRG. Otherwise it optimizes the HRG log-likelihood
first, and then samples starting from the optimum.consensus_tree(graph, hrg = NULL, start = FALSE, num.samples = 10000)
igraphHRG
object. consensus_tree
allows this to be
NULL
as well, then a HRG is fitted to the graph first, from a
random starting point.igraphHRG
object, or from a random starting point.consensus_tree
returns a list of two objects. The first
is an igraphHRGConsensus
object, the second is an
igraphHRG
object. The igraphHRGConsensus
object has the
following members:parents
vector.fit_hrg
,
hrg.fit
; hrg-methods
;
hrg.game
, sample_hrg
;
hrg.predict
, predict_edges
;
hrg_tree
; hrg
,
hrg.create
;
print.igraphHRGConsensus
;
print.igraphHRG