View source: R/stages_hclust.R
stages_hclust | R Documentation |
Build a stage event tree with k
stages for each variable by
clustering stage probabilities with hierarchical clustering.
stages_hclust(
object,
distance = "totvar",
k = NA,
method = "complete",
ignore = object$name_unobserved,
limit = length(object$tree),
scope = NULL,
score = function(x) {
return(-BIC(x))
}
)
object |
an object of class |
distance |
character, the distance measure to be used, either
a possible |
k |
integer or (named) vector: number of clusters, that is stages per variable.
Values will be recycled if needed. If |
method |
the agglomeration method to be used in |
ignore |
vector of stages which will be ignored and left untouched.
By default the name of the unobserved stages stored in
|
limit |
the maximum number of variables to consider. |
scope |
names of the variables to consider. |
score |
A function. Score to maximize for automatic selection
of the number of stages. Used if |
hclust_sevt
performs hierarchical clustering
of the initial stage probabilities in object
and it aggregates them into the specified number
of stages (k
).
A different number of stages for the different variables
in the model can be specified by supplying a (named) vector
via the argument k
.
If k
is NA
for some variables, all
possible number of stages will be checked and the
one that maximize the score
will be selected.
A staged event tree object.
data("Titanic")
model <- stages_hclust(full(Titanic, join_unobserved = TRUE, lambda = 1), k = 2)
summary(model)
### or search k via BIC minimization
model1 <- stages_hclust(full(Titanic), k = NA)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.