Datasets: Series of function to simulate data.

Description

These functions generates data with multiple groups using different distributions and optionnaly adding a level of missing value.

Usage

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)

Value

list of data.frame simulated according to the function parameters.

Arguments

X: The X matrix or data.frame for the measurement part of the model
Y: The Y matrix or data.frame for the structural part of the model
nan_ratio: The ratio of missing values. A value between 0 and 1.
random_state: An integer initializing the seed of the random generator.
n_classes: Number of latent classes required.
n_mm: Number of features in the measurement model.
sep_level: Separation level in the measurement data.
n_samples: Number of samples.

Author

Éric Lacourse, Roxane de la Sablonnière, Charles-Édouard Giguère, Sacha Morin, Robin Legault, Félix Laliberté, Zsusza Bakk

Details

These function returns simulated data used to test the package.

References

Bakk, Z. and Kuha, J. Two-step estimation of models between latent classes and external variables. Psychometrika, 83(4):871-892, 2018