Cut a Factor Merger Tree
Splits factor levels into non-overlapping clusters
based on a factorMerger object.
If a stat is "loglikelihood" or "p-value"
then performs bottom-up search through models
on the merging path until spots a model scored worse
than the given threshold (value).
If stat = "GIC", value is interpreted as
GIC penalty and optimal GIC model is returned..
cutTree(factorMerger, stat = "GIC", value = 2)
Arguments
| factorMerger | object of a class |
|---|---|
| stat | statistic used in the bottom-up search. Available statistics are:
|
| value | cut threshold or penalty (for GIC) |
Value
Returns a factor vector - each observation is given a new cluster label.
Details
By default, cutree returns factor partition
corresponding to the optimal GIC model (with the lowest GIC).