data_sim {heteromixgm}

data_sim

Description

Simulate mixed multi-group data.

Usage

data_sim(network, n, p, K, ncat, rho, gamma_g = NULL, gamma_o, gamma_b = NULL,
gamma_p = NULL, prob = NULL, nclass = NULL)

Arguments

network

Type of network, either "circle", "Random", "Cluster", "Scale-free", "AR1" or "AR2".

n

Number of observations.

p

Number of variables.

K

Number of groups.

ncat

Number of categories for ordinal variables.

rho

Dissimilarity parameter inducing dissimilarity between the K datasets.

gamma_g

Proportion of Gaussian variables in the data.

gamma_o

Proportion of ordinal variables in the data.

gamma_b

Proportion of binomial variables in the data.

gamma_p

Proportion of Poisson variables in the data..

prob

Edge occurency probability in random graph.

nclass

Number of clusters in cluster graph.

Value

z

A list of K n by p matrices representing the latent Gaussian transformed (observed) data.

theta

A list of K n by p matrices representing the precision matrices corresponding to the latent Gaussian (unobserved) data.

Author(s)

Sjoerd Hermes, Joost van Heerwaarden and Pariya Behrouzi
Maintainer: Sjoerd Hermes [e-mail]

References

1. Hermes, S., van Heerwaarden, J., and Behrouzi, P. (2022). Copula graphical models for heterogeneous mixed data. arXiv preprint, arXiv:2210.13140.

Examples

data_sim(network = "Random", n = 10, p = 50, K = 3, ncat = 6, rho = 0.25,
gamma_o = 0.5, gamma_b = 0.1, gamma_p = 0.2, prob = 0.05)