code: def test_multivariate_unequal_intensities():
      T = np.random.exponential(10, size=300)
      g = np.random.binomial(2, 0.5, size=300)
      T[g == 1] = np.random.exponential(1, size=(g == 1).sum())
      result = stats.multivariate_logrank_test(T, g)
      assert result.p_value < 0.05
  
imports: import numpy
  import pandas
  import numpy.testing
  import pytest
  from pandas.testing import assert_frame_equal
  from lifelines import statistics
  from lifelines import CoxPHFitter, KaplanMeierFitter, WeibullFitter
  from lifelines.exceptions import StatisticalWarning
  from lifelines.datasets import load_waltons, load_g3, load_lymphoma, load_dd, load_regression_dataset, load_leukemia
label_desc: Use image node_id 21 for calling a global function with example usage: test_multivariate_unequal_intensities() without return types