update_z

A character value corresponding to id column name

col_id

A character value corresponding to the target variable

target

A matrix of estimated beta in a specific cluster k

beta_up

A list of dataframe filter by id levels

df_id

A list of design matrices filter by id levels

matrix_id

M-step : Update the matrix of working variables Z from beta iterative equation

Provides a clustering method of non-gaussian longitudinal data with a mixture of generalized linear models. The longitudinal data should be defined as repeated observations for each individual. The number of observations for each individual can be different. In runEM(), an expectation-maximization algorithm is developed for both binomial and longitudinal data mixture model.

update_z: M-step : Update the matrix of working variables Z from beta iterative equation

Description

Usage

Arguments

Value