pyuncertainnumber.pba.cbox_constructor¶

a Cbox constructor by Leslie

Classes¶

Cbox

Confidence boxes (c-boxes) are imprecise generalisations of traditional confidence distributions

Functions¶

`cbox_from_extredists`(rvs[, shape, extre_bound_params])	define cbox via parameterised extreme bouding distrbution functions
`cbox_from_pseudosamples`(samples)

Module Contents¶

class pyuncertainnumber.pba.cbox_constructor.Cbox(*args, extre_bound_params=None, **kwargs)¶

Confidence boxes (c-boxes) are imprecise generalisations of traditional confidence distributions

They have a different interpretation to p-boxes but rely on the same underlying mathematics. As such in pba-for-python c-boxes inhert most of their methods from Pbox.

Parameters:: Pbox (_type_) – _description_

extre_bound_params = None¶

__repr__()¶

display(parameter_name=None, **kwargs)¶

ci(c=0.95, alpha=None, beta=None, style='two-sided')¶: query the confidence interval at a given confidence level c

pyuncertainnumber.pba.cbox_constructor.cbox_from_extredists(rvs, shape=None, extre_bound_params=None)¶

define cbox via parameterised extreme bouding distrbution functions

Parameters:

rvs (list) – list of scipy.stats.rv_continuous objects
extre_bound_params (list) – list of parameters for the extreme bounding c.d.f

pyuncertainnumber.pba.cbox_constructor.cbox_from_pseudosamples(samples)¶