statsmodels.emplike.descriptive.DescStatUV.ci_var

DescStatUV.ci_var(lower_bound=None, upper_bound=None, sig=0.05)

Returns the confidence interval for the variance.

Parameters

lower_boundfloat

The minimum value the lower confidence interval can take. The p-value from test_var(lower_bound) must be lower than 1 - significance level. Default is .99 confidence limit assuming normality

upper_boundfloat

The maximum value the upper confidence interval can take. The p-value from test_var(upper_bound) must be lower than 1 - significance level. Default is .99 confidence limit assuming normality

sigfloat

The significance level. Default is .05

Returns

Intervaltuple

Confidence interval for the variance

Notes

If the function returns the error f(a) and f(b) must have different signs, consider lowering lower_bound and raising upper_bound.

Examples

>>> import numpy as np
>>> import statsmodels.api as sm
>>> random_numbers = np.random.standard_normal(100)
>>> el_analysis = sm.emplike.DescStat(random_numbers)
>>> el_analysis.ci_var()
(0.7539322567470305, 1.229998852496268)
>>> el_analysis.ci_var(.5, 2)
(0.7539322567469926, 1.2299988524962664)