optimizer_batch: Fitting clusterwise linear mixed effects model on a given...

In Redha-ALLICHE/clusterwiselmm: Apply geometrical clusterwise to linear multi-level models (lmm)

Description

run clusterwise linear mixed effects model with K clusters on the given data. This function uses a batch approach where the cost are calculated along all rows and the affectation is made to minimize this cost, after that the k models are adjusted.

Usage

optimizer_batch(
  data,
  target,
  K,
  formula,
  nb_iterations = 100,
  initialization = NULL
)

Arguments

data	data frame containing the variables named in formula.
target	vector containing the target variable.
K	number of clusters.
formula	a two sided linear formula object corresponding to formula parameter in lmer from lme4 package.
nb_iterations	maximum number of iterations.
initialization	if vector of the same length of data, use this vector as clustering initialization. Otherwise, do a random initialization.

Value

list containing the models as a class of clmm, the final clustering and the final cost.

Redha-ALLICHE/clusterwiselmm documentation built on Aug. 3, 2020, 1:10 a.m.