Samples a tree, either by permuting the labels (which is usefull for
a permutation test), or by repeated sampling of the same labels (essential
for bootstraping when we don't have access to the original data which
produced the tree).
Duplicates a leaf in a tree. Useful for non-parametric bootstraping trees
since it emulates what would have happened if the tree was constructed based
on a row-sample with replacments from the original data matrix.
logical (FALSE). Should we shuffle the labels (if FALSE),
or should we replicate the same leaf over and over, while omitting other
leaves? (this is when set to TRUE).
dend_labels
a character vector of the tree's labels.
This can save the time it takes for getting the tree labels (in case we run
a simulating, computing this once might save some running time).
If missing, it uses labels in order to get the labels.
sampled_labels
a character vector of the tree's sampled labels.
This can help us if we wish to compare two trees. In such a case we'd like
to be able to have the same sample of labels used on both trees.
If missing, it uses sample in order to get the sampled labels.
Only works when replace=TRUE!
fix_members
logical (TRUE). Fix the number of members in attr
using fix_members_attr.dendrogram
fix_order
logical (TRUE). Fix the leaves order
fix_midpoint
logical (TRUE). Fix the midpoint value.
If TRUE, it overrides "fix_members" and turns it into TRUE (since it must
have a correct number of members in order to work).
values using rank_order.dendrogram
...
not used
Value
A dendrogram, after "sampling" its leaves.
See Also
sample, duplicate_leaf
Examples
## Not run:
# define dendrogram object to play with:
dend <- USArrests[1:5,] %>% dist %>% hclust(method = "ave") %>% as.dendrogram
plot(dend)
# # same tree, with different order of labels
plot(sample.dendrogram(dend, replace = FALSE))
# # A different tree (!), with some labels duplicated,
# while others are pruned
plot(sample.dendrogram(dend, replace = TRUE))
## End(Not run)