'Calculate the power of a chisquare test for one sample
Only two-sided alternative is implemented
Parameters
effect_size : float
standardized effect size, according to Cohen\'s definition.
see :func:`statsmodels.stats.gof.chisquare_effectsize`
nobs : int or float
sample size, number of observations.
alpha : float in interval (0,1)
significance level, e.g. 0.05, is the probability of a type I
error, that is wrong rejections if the Null Hypothesis is true.
n_bins : int
number of bins or cells in the distribution.
Returns
power : float
Power of the test, e.g. 0.8, is one minus the probability of a
type II error. Power is the probability that the test correctly
rejects the Null Hypothesis if the Alternative Hypothesis is true.'

def power(self, effect_size, nobs, alpha, n_bins, ddof=0):

    from statsmodels.stats.gof import chisquare_power
    return chisquare_power(effect_size, nobs, n_bins, alpha, ddof=0)
