maxent: Compute Maximum Entropy Distributions
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.
Downloads
- maxent-0.6.0.1.tar.gz [browse] (Cabal source package)
- Package description (as included in the package)
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Versions [RSS] | 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 |
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Dependencies | ad (>=3.4 && <3.5), base (>=4.6 && <4.7), lagrangian (>=0.5 && <0.6), nonlinear-optimization (>=0.3 && <0.4), vector (>=0.10 && <0.11) [details] |
License | BSD-3-Clause |
Author | Jonathan Fischoff |
Maintainer | jonathangfischoff@gmail.com |
Category | Math |
Home page | https://github.com/jfischoff/maxent |
Uploaded | by JonathanFischoff at 2013-03-13T23:02:39Z |
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Reverse Dependencies | 1 direct, 0 indirect [details] |
Downloads | 8186 total (54 in the last 30 days) |
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