ricardoV94

from pylab import *
from scipy.stats import uniform, binom, expon, beta

true_gamma = 0.5

N = 600
T = 15
data = zeros((2, N), dtype=float)
event_times = data[0,:]
event_times[:] = uniform(0,15).rvs(N)

ricardoV94

import numpy as np
from scipy import stats
from itertools import combinations
from statsmodels.stats.multitest import multipletests
from statsmodels.stats.libqsturng import psturng
import warnings


def kw_dunn(groups, to_compare=None, alpha=0.05, method='bonf'):
    """