2.3.1. dodiscover.ci.GSquareCITest

class dodiscover.ci.GSquareCITest(data_type='binary', levels=None)

Methods

test(df, x_vars, y_vars[, z_covariates])

Abstract method for all conditional independence tests.

test(df, x_vars, y_vars, z_covariates=None)

Abstract method for all conditional independence tests.

Parameters:

dfpd.DataFrame

The dataframe containing the dataset.

x_varsSet of column

A column in df.

y_varsSet of column

A column in df.

z_covariatesSet, optional

A set of columns in df, by default None. If None, then the test should run a standard independence test.

Returns:

statfloat

The test statistic.

pvaluefloat

The p-value of the test.

2.3.1.1. Examples using dodiscover.ci.GSquareCITest

Basic causal discovery with DoDiscover using the PC algorithm

Basic causal discovery with DoDiscover using the PC algorithm

Causal discovery with interventional data - Sachs dataset

Causal discovery with interventional data - Sachs dataset