Multivariate binary data in python

This script generates multivariate and correlated binary data using the procedure outlined in

On the Generation of Correlated Artificial Binary Data
Friedrich Leisch, Andreas Weingessel, Kurt Hornik (1998)

and implemented in the R package bindata.

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Replicating Example 1 in the original paper:

from mvbin import mvbin
import numpy as np

# The joint probability matrix:
joint_prob = np.array([[0.2, 0.05, 0.15],
                       [0.05, 0.5, 0.45],
                       [0.15, 0.45, 0.8]])
p = np.diag(joint_prob)

# Population correlation matrix::
corr = np.array([[1., -0.25, -0.0625],
                 [-0.25, 1., 0.25],
                 [-0.0625, 0.250, 1.]])

# Sample:
sample = mvbin(p=np.diag(joint_prob),
               joint_prob=joint_prob,
               size=10000)

# Sample correlation:
print(np.corrcoef(sample, rowvar=False))

Which gives us the following sample correlation:

[[ 1.         -0.25164281 -0.06168207]
 [-0.25164281  1.          0.25074679]
 [-0.06168207  0.25074679  1.        ]]