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Predictions with Markov Chains is a JS application that multiplies a probability vector with a transition matrix multiple times (n steps - user defined). On each step, the values from the resulting probability vectors are plotted on a chart. The resulting curves on the chart indicate the behavior of the system over n steps.

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Predictions with Markov Chains

This JS application multiplies a probability vector with a transition matrix multiple times (n steps - user defined). On each step, the values from the resulting probability vectors are plotted on a chart. The resulting curves on the chart indicate the behavior of the system over n steps. Note that the application allows a prediction for systems with a maximum of 13 states. However, more states can be added. The application has no dependencies and can be used as a single offline html file. Note that the construction and theory behind the chart of this application can be found here.

Live demo: https://gagniuc.github.io/Predictions-with-Markov-Chains/

References

  • Paul A. Gagniuc. Algorithms in Bioinformatics: Theory and Implementation. John Wiley & Sons, Hoboken, NJ, USA, 2021, ISBN: 9781119697961.

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Predictions with Markov Chains is a JS application that multiplies a probability vector with a transition matrix multiple times (n steps - user defined). On each step, the values from the resulting probability vectors are plotted on a chart. The resulting curves on the chart indicate the behavior of the system over n steps.

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