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SMML codelength for data from the binomial distribution

version 1.0.0 (3.16 KB) by Statovic
This is an implementation of the polynomial time algorithm for computing the SMML codelength for data from the binomial distribution.

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Updated 15 Sep 2020

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Strict Minimum Message Length (SMML) is criterion for statistical inference based on information theory. For general statistical models computing the SMML codelength of a model is NP-hard. This function implements the dynamic programming algorithm of Farr and Wallace (see [1]) that computes the SMML codelength for the binomial distribution in polynomial time. We assume a uniform prior on the probability of success. The algorithm is equivalent to Dijkstra's shortest path algorithm. For details on the algorithm and SMML, please see [1].

Code examples:
smml_binomial(5);
[P, msglen] = smml_binomial(10);

References:
[1] Farr, G. E.; Wallace, C. S.
The Complexity of Strict Minimum Message Length Inference
Computer Journal; May 2002, Vol. 45 Issue 3, p285

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MATLAB Release Compatibility
Created with R2020a
Compatible with any release
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