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NotesParametersReturns
rv_generic.interval(self, confidence=None, *args, **kwds)

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).

Parameters

confidence : array_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).

loc : array_like, optional

location parameter, Default is 0.

scale : array_like, optional

scale parameter, Default is 1.

Returns

a, b : ndarray of float

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

Confidence interval with equal areas around the median.

Examples

See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


GitHub : /scipy/stats/_distn_infrastructure.py#1480
type: <class 'function'>
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