hmmus Hidden Markov model stuff
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algorithms Markov Model Markov HMM algorithms HMM

hmmus Description

Hidden Markov model stuff The hmmus project has some HMM algorithms implemented in C, and it is meant to be useful under the following conditions:* The sequence of observations to be analyzed is so long that it does not fit conveniently in RAM.* Likelihoods per hidden state per position have been precalculated.* Numerical stability is important, but is not so important that error bounds on the output are required.* The number of hidden states is small.* The matrix of probabilities of transitions between hidden states is dense.* Binary data files are acceptable as input and output.This project would be especially useless in the following cases:* User friendly or pedagogically informative software is desired.* All of the data can fit in RAM and numerical stability is not an issue.* The hidden state transitions are defined by a large sparse graph.* The emission distributions are uncomplicated (e.g. finite or normal).Operating system requirements:* This project was developed using Ubuntu, so it will probably work on Debian-based Linux distributions.* It might work with non-Debian-based Unix variants.* It probably will not work on Windows.Major dependencies:* A C compiler which is not too different from gcc. Requirements: · Python · Argparse

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