These functions generates data with multiple groups using different distributions and optionnaly adding a level of missing value.
random_nan(X, Y, nan_ratio, random_state=NULL)
bakk_measurements(n_classes, n_mm, sep_level)
data_bakk_response(n_samples, sep_level, n_classes = 3, n_mm = 6, random_state = NULL)
data_bakk_covariate(n_samples, sep_level, n_mm = 6, random_state = NULL)
data_bakk_complete(n_samples, sep_level, n_mm=6, random_state=NULL, nan_ratio=0.0)
data_generation_gaussian(n_samples, sep_level, n_mm=6, random_state=NULL)
data_gaussian_diag(n_samples, sep_level, n_mm = 6, random_state = NULL, nan_ratio = 0.0)
list of data.frame simulated according to the function parameters.
The X matrix or data.frame for the measurement part of the model
The Y matrix or data.frame for the structural part of the model
The ratio of missing values. A value between 0 and 1.
An integer initializing the seed of the random generator.
Number of latent classes required.
Number of features in the measurement model.
Separation level in the measurement data.
Number of samples.
Éric Lacourse, Roxane de la Sablonnière, Charles-Édouard Giguère, Sacha Morin, Robin Legault, Félix Laliberté, Zsusza Bakk
These function returns simulated data used to test the package.
Bakk, Z. and Kuha, J. Two-step estimation of models between latent classes and external variables. Psychometrika, 83(4):871-892, 2018