statsmodels.emplike.descriptive.DescStatUV.test_var¶

DescStatUV.test_var(sig2_0, return_weights=False)[source]¶

Returns -2 x log-likelihood ratio and the p-value for the hypothesized variance

Parameters:

sig2_0float: Hypothesized variance to be tested
return_weightsbool: If True, returns the weights that maximize the likelihood of observing sig2_0. Default is False

Returns:

test_resultstuple: The log-likelihood ratio and the p_value of sig2_0

Examples

>>> import numpy as np
>>> import statsmodels.api as sm
>>> random_numbers = np.random.standard_normal(1000)*100
>>> el_analysis = sm.emplike.DescStat(random_numbers)
>>> hyp_test = el_analysis.test_var(9500)