# maxent: Compute Maximum Entropy Distributions

[ bsd3, library, math ] [ Propose Tags ]

The maximum entropy method, or MAXENT, is variational approach for computing probability distributions given a list of moment, or expected value, constraints.

Here are some links for background info.

A good overview of applications: http://cmm.cit.nih.gov/maxent/letsgo.html

On the idea of maximum entropy in general: http://en.wikipedia.org/wiki/Principle_of_maximum_entropy

Use this package to compute discrete maximum entropy distributions over a list of values and list of constraints.

Here is a the example from Probability the Logic of Science

> maxent 0.00001 [1,2,3] [average 1.5]
Right [0.61, 0.26, 0.11]

The classic dice example

> maxent 0.00001 [1,2,3,4,5,6] [average 4.5]
Right [.05, .07, 0.11, 0.16, 0.23, 0.34]

One can use different constraints besides the average value there.

Versions [RSS] [faq] 0.1.0.0, 0.1.0.1, 0.2.0.0, 0.2.0.1, 0.3.0.1, 0.3.1.1, 0.4.0.0, 0.6.0.0, 0.6.0.1, 0.6.0.3, 0.6.0.4, 0.7 ad (==4.*), base (>=4.5 && <5), lagrangian (==0.6.*), nonlinear-optimization (==0.3.*), vector (==0.10.*) [details] BSD-3-Clause (c) Jonathan Fischoff 2012-2014, (c) Eric Pashman 2014 jonathangfischoff@gmail.com Math https://github.com/jfischoff/maxent by JonathanFischoff at 2014-10-09T07:22:54Z NixOS:0.7 7379 total (56 in the last 30 days) (no votes yet) [estimated by Bayesian average] λ λ λ Docs uploaded by userBuild status unknown

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