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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 \u003ci\u003en\u003c/i\u003e steps. Note that the application allows a prediction for systems with a maximum of four states. [This version in JS](https://gagniuc.github.io/Predictions-with-Markov-Chains/) can also be of use: [Predictions with Markov Chains](https://github.com/Gagniuc/Predictions-with-Markov-Chains).\n\n![screenshot](https://github.com/Gagniuc/Markov-Chains-Prediction-framework/blob/main/img/Markov%20Chains%20-%20Prediction%20framework.png?raw=true)\n\n![screenshot](https://github.com/Gagniuc/Markov-Chains-Prediction-framework/blob/main/img/Markov%20Chains%20-%20Prediction%20framework%20(new%20setup).png?raw=true)\n\n# References\n\n- \u003ci\u003ePaul A. Gagniuc. Markov chains: from theory to implementation and experimentation. Hoboken, NJ,  John Wiley \u0026 Sons, USA, 2017, ISBN: 978-1-119-38755-8.\u003c/i\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgagniuc%2Fmarkov-chains-prediction-framework","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgagniuc%2Fmarkov-chains-prediction-framework","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgagniuc%2Fmarkov-chains-prediction-framework/lists"}