prop.part
counts the number of bipartitions found in a series
of trees given as ...
.
prop.clades
counts the number of times the bipartitions present
in phy
are present in a series of trees given as ...
or
in the list previously computed and given with part
.
boot.phylo
performs a bootstrap analysis.
boot.phylo(phy, x, FUN, B = 100, block = 1)
prop.part(...)
prop.clades(phy, ..., part = NULL)
## S3 method for class 'prop.part':
print(x, ...)
## S3 method for class 'prop.part':
summary(object, ...)
"phylo"
.boot.phylo
: a taxa (rows) by characters
(columns) matrix; this may be presented as a list; in the case of
print
: an object of class "prop.part"
.phy
(see details).x
that will be resampled
together (see details)."phylo"
, (ii) a
series of such objects separated by commas, or (iii) a list
containing such objects.prop.part
; if
this is used then ...
is ignored."prop.part"
.prop.part
returns an object of class "prop.part"
which
is a list with an attribute "number"
. The elements of this list
are the observed clades, and the attribute their respective numbers. prop.clades
and boot.phylo
returns a numeric vector
which ith element is the number associated to the ith
node of phy
.
FUN
in boot.phylo
must be the function used
to estimate the tree from the original (resampled) data matrix. Thus,
if the tree is estimated with neighbor-joining (see nj
), one
maybe wants something like FUN = function(xx) nj(dist.dna(xx))
. block
in boot.phylo
specifies the number of columns to
be resampled altogether. For instance, if one wants to resample at the
codon-level, then block = 3
must be used.
Felsenstein, J. (1985) Confidence limits on phylogenies: an approach using the bootstrap. Evolution, 39, 783--791.
dist.topo
, consensus