statsmodels.distributions.discrete.DiscretizedCount.interval¶

DiscretizedCount.interval(confidence, *args, **kwds)¶

Confidence interval with equal areas around the median.

Parameters:¶

confidencearray_like of float

Probability that an rv will be drawn from the returned range. Each value should be in the range [0, 1].

arg1, arg2, …array_like

The shape parameter(s) for the distribution (see docstring of the instance object for more information).

locarray_like, optional

location parameter, Default is 0.

scalearray_like, optional

scale parameter, Default is 1.

Returns:¶

a, bndarray of float

end-points of range that contain 100 * alpha % of the rv’s possible values.

Notes

This is implemented as ppf([p_tail, 1-p_tail]), where ppf is the inverse cumulative distribution function and p_tail = (1-confidence)/2. Suppose [c, d] is the support of a discrete distribution; then ppf([0, 1]) == (c-1, d). Therefore, when confidence=1 and the distribution is discrete, the left end of the interval will be beyond the support of the distribution. For discrete distributions, the interval will limit the probability in each tail to be less than or equal to p_tail (usually strictly less).