get_clusters {longmixr}

Extract the cluster assignments

Description

This functions extracts the cluster assignments from an lcc object. One can specify which for which number of clusters the assignments should be returned.

Usage

get_clusters(cluster_solution, number_clusters = NULL)

Arguments

cluster_solution

an lcc object

number_clusters

default is NULL to return all assignments. Otherwise specify a numeric vector with the number of clusters for which the assignments should be returned, e.g. 2:4

Value

a data.frame with an ID column (the name of the ID column was specified by the user when calling the longitudinal_consensus_cluster) function and one column with cluster assignments for every specified number of clusters. Only the assignments included in number_clusters are returned in the form of columns with the names assignment_num_clus_x

Examples

# not run
set.seed(5)
test_data <- data.frame(patient_id = rep(1:10, each = 4),
visit = rep(1:4, 10),
var_1 = c(rnorm(20, -1), rnorm(20, 3)) +
rep(seq(from = 0, to = 1.5, length.out = 4), 10),
var_2 = c(rnorm(20, 0.5, 1.5), rnorm(20, -2, 0.3)) +
rep(seq(from = 1.5, to = 0, length.out = 4), 10))
model_list <- list(flexmix::FLXMRmgcv(as.formula("var_1 ~ .")),
flexmix::FLXMRmgcv(as.formula("var_2 ~ .")))
clustering <- longitudinal_consensus_cluster(
data = test_data,
id_column = "patient_id",
max_k = 2,
reps = 3,
model_list = model_list,
flexmix_formula = as.formula("~s(visit, k = 4) | patient_id"))
cluster_assignments <- get_clusters(clustering, number_clusters = 2)
# end not run