Generate Multivariate Ordinal and Binary data.
gen_ordinal(n, p, levels = 2, cor_mat, empirical = FALSE)
| n | Number of observations (n). |
|---|---|
| p | Number of variables (p). |
| levels | Number of categories (defaults to 2; binary data). |
| cor_mat | A p by p matrix including the true correlation structure. |
| empirical | Logical. If true, |
A n by p data matrix.
In order to allow users to enjoy the functionality of BGGM, we had to make minor changes to the function rmvord_naiv
from the R package orddata (Leisch et al. 2010)
. All rights to, and credit for, the function rmvord_naiv
belong to the authors of that package.
This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. A copy of the GNU General Public License is available at https://www.R-project.org/Licenses.
Leisch F, Kaiser AWS, Hornik K (2010). orddata: Generation of Artificial Ordinal and Binary Data. R package version 0.1/r4, https://R-Forge.R-project.org/projects/orddata/.
################################ ######### example 1 ############ ################################ main <- ptsd_cor1[1:5,1:5] p <- ncol(main) pcors <- -(cov2cor(solve(main)) -diag(p)) diag(pcors) <- 1 pcors <- ifelse(abs(pcors) < 0.05, 0, pcors) inv <- -pcors diag(inv) <- 1 cors <- cov2cor( solve(inv)) # example data Y <- BGGM::gen_ordinal(n = 500, p = 5, levels = 2, cor_mat = cors, empirical = FALSE) ################################ ######### example 2 ############ ################################ # empirical = TRUE Y <- gen_ordinal(n = 500, p = 16, levels = 5, cor_mat = ptsd_cor1, empirical = TRUE)