# G-Square test

Perform an independence test using G-Square test 1. This test is based on the log likelihood ratio test.

## Usage

    from causal-learn.utils.cit import gsq
    p = gsq(data, X, Y, conditioning_set)

## Parameters

data: data matrices.

X, Y and condition_set: data matrices of size number_of_samples * dimensionality.

G_sq: True means using G-Square test; False means using Chi-Square test.

## Returns

p: the p-value of the test

1

  Tsamardinos, I., Brown, L. E., & Aliferis, C. F. (2006). The max-min hill-climbing Bayesian network structure learning algorithm. Machine learning, 65(1), 31-78.