stages_hclust: Learn a staged tree with hierarchical clustering

In stagedtrees: Staged Event Trees

Learn a staged tree with hierarchical clustering

Description

Build a stage event tree with k stages for each variable by clustering stage probabilities with hierarchical clustering.

Usage

stages_hclust(
  object,
  distance = "totvar",
  k = length(object$tree[[1]]),
  method = "complete",
  ignore = object$name_unobserved,
  limit = length(object$tree),
  scope = NULL
)

Arguments

object	an object of class sevt with fitted probabilities and data, as returned by full or sevt_fit.
distance	character, the distance measure to be used, either a possible method for dist or one of the following: "totvar", "hellinger".
k	integer or (named) vector: number of clusters, that is stages per variable. Values will be recycled if needed.
method	the agglomeration method to be used in hclust.
ignore	vector of stages which will be ignored and left untouched, by default the name of the unobserved stages stored in object$name_unobserved.
limit	the maximum number of variables to consider.
scope	names of the variables to consider.

Details

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.

Value

A staged event tree object.

Examples

data("Titanic")
model <- stages_hclust(full(Titanic, join_unobserved = TRUE, lambda = 1), k = 2)
summary(model)

stagedtrees documentation built on April 29, 2022, 1:06 a.m.