Skip to main content

Utility functions related to the Cash statistic

Project description



Utility functions related to the Cash statistic

The Poisson distribution is

P(x|mu) = exp(-mu) mu^x / x!

The Cash statistic is defined to be the model (mu) dependent part of -2ln(P), analogous to the role that chi^2 plays for the Gaussian distribution,

C = 2( mu - x*ln(mu) ).

A modified version,

C_m = 2( mu - x + x*ln(x/mu) ),

is equivalent to C for parameter inference (i.e. has the same dependence on mu), and also has the nice property of becoming equivalent to chi^2 when x is large. Kaastra (2017) was kind enough to provide approximate expressions for the mean and variance of C_m, which can be used to determine whether the actual C_m corresponding to a fitted model is indicative of a good fit (just as chi^2 does for the Gaussian distribution).

This package contains python code to calculate C, C_m, and the theoretical mean and variance of C_m. The GitHub repo contains implementations in other languages.

Project details

Download files

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

Source Distribution

cashstatistic-0.1.3.tar.gz (4.3 kB view hashes)

Uploaded source

Built Distribution

cashstatistic-0.1.3-py3-none-any.whl (4.1 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page