Markov chains can be used to produce forecasts in probabilistic terms, when a sufficient number of statistical data can be obtained about the interrelations between some events. This is done through the construction of a Markovian matrix, usable to detect statistical degrees of correlations.
The underlying assumption is that the observed transition probabilities reflect some lax, but general, determinisms binding some events to some others, according to variable circumstances.
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Bertalanffy Center for the Study of Systems Science (2020). Title of the entry. In Charles François (Ed.), International Encyclopedia of Systems and Cybernetics (2). Retrieved from www.systemspedia.org/[full/url]
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