rmvbinary_QA {RepeatedHighDim} | R Documentation |
Simulating correlated binary variables using the algorithm by Qaqish (2003)
Description
Generation of random sample of binary correlated variables
Usage
rmvbinary_QA(n, R, p)
Arguments
n |
Sample size |
R |
Correlation matrix |
p |
Vector of marginal probabilities |
Details
The function implements the algorithm proposed by Qaqish (2003) to generate a random sample of d (=length(p)) correlated binary variables. The sample is generated based on given marginal probabilities p of the d variables and their correlation matrix R. The algorithm starts by generating a data for the first variable X_1 and generates succesively the data for X_2, ... based on their conditional probabilities P(X_j|X_[i-1],...,X_1), j=1,...,d.
Value
Sample (n x p)-matrix representing a random sample of size n from the specified multivariate binary distribution.
Author(s)
Jochen Kruppa, Klaus Jung
References
Qaqish, B. F. (2003) A family of multivariate binary distributions for simulating correlated binary variables with specified marginal means and correlations. Biometrika, 90(2), 455-463. doi:10.1093/biomet/90.2.455
See Also
For more information, please refer to the package's documentation and the tutorial: https://software.klausjung-lab.de/.
Examples
## Generation of a random sample
rmvbinary_QA(n = 10, R = diag(2), p = c(0.5, 0.6))