rmvbinary_EP {RepeatedHighDim} | R Documentation |
Simulating correlated binary variables using the algorithm by Emrich and Piedmonte (1991)
Description
Generation of random sample of binary correlated variables
Usage
rmvbinary_EP(n, R, p)
Arguments
n |
Sample size |
R |
Correlation matrix |
p |
Vector of marginal probabilities |
Details
The function implements the algorithm proposed by Emrich and Piedmonte (1991) 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 generates first determines an appropriate correlation matrix R' for the multivariate normal distribution. Next, a sample is drawn from N_d(0, R') and each variable is finnaly dichotomized with respect to p.
Value
Sample (n x p)-matrix with representing a random sample of size n from the specified multivariate binary distribution.
Author(s)
Jochen Kruppa, Klaus Jung
References
Emrich, L.J., Piedmonte, M.R. (1991) A method for generating highdimensional multivariate binary variates. The American Statistician, 45(4), 302. doi:10.1080/00031305.1991.10475828
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_EP(n = 10, R = diag(2), p = c(0.5, 0.6))