Skip to main content

No project description provided

Project description

This is a probability bound analysis library for Python

Intervals can be specified by using pba.I(x,y)

Probability distributions can be specified using pba.distname(**args) for all distribution that scipy.stats supports. Using interval arguments return p-boxes

K out of N confidence boxes can be specified using pba.KN(k,n)

+,-,*,/ operations are supported. By default frechet convolutions are used. But independant, perfect and opposite convolutions are also supported, they can be specified using a letter as in:

A.add(B, method = 'o') # A + B using opposite convolutions
C.sub(D, method = 'p') # C - D using perfect convolutions
E.mul(F, method = 'i') # E * F using independence convolutions
G.div(H, method = 'f') # G / H using frechet convolutions

Note: currently there may be errors in creating p-boxes for certain distribution types because of the way arguments are passed to the distributions in scipy.stats library. If these errors are noticed please email me

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for pba, version 0.6.0
Filename, size File type Python version Upload date Hashes
Filename, size pba-0.6.0.tar.gz (12.1 kB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring DigiCert DigiCert EV certificate Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page