statsmodels.emplike.descriptive.DescStatUV.test_var#

DescStatUV.test_var(sig2_0, return_weights=False, *, result_object=None)[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, optional: If True, returns the weights that maximize the likelihood of observing sig2_0. Default is False
result_objectbool, optional: Flag indicating whether to return the results as an EmpLikeTestResult NamedTuple instead of a plain tuple. When return_weights=True the NamedTuple holds the same three elements as the legacy tuple, so it unpacks identically and is always returned, with no warning. When return_weights=False the legacy two-element tuple is returned by default and a FutureWarning is issued.

Deprecated since version 0.15.0: In release 0.16.0 or after July 2027, whichever is later, the default will change to always return an EmpLikeTestResult. Set result_object=True to opt in now, or result_object=False to silence the warning and keep the current return type.

Returns:

EmpLikeTestResult or tuple

If result_object=True or return_weights=True, a NamedTuple with fields llr, pvalue and weights. See EmpLikeTestResult.

Otherwise (the deprecated default), the plain (llr, pvalue) tuple.

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, result_object=True)