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Markov chains can pop up everywhere. Not shown in this excellent intro is that the stationary distribution can be calculated as the eigenvector with an eigenval
by tlarkworthy 13y ago
Markov chains can pop up everywhere. Not shown in this excellent intro is that the stationary distribution can be calculated as the eigenvector with an eigenvalue of 1.
I have used them in practice for load testing. Have thousands of bots randomly take actions using a transition table. The aggregate behaviour can predicted and converted into the frequency domain using the above trick and some other stuff (http://edinburghhacklab.com/2014/03/taming-randomized-load-testing-2/ http://edinburghhacklab.com/2014/03/taming-randomized-load-t...)
- eoinmurray92 13y agoI think you mean eigenvalue of 0 for the stationary distribution.
- tlarkworthy 13y agono http://en.wikipedia.org/wiki/Markov_chain#Stationary_distribution_relation_to_eigenvectors_and_simplexes http://en.wikipedia.org/wiki/Markov_chain#Stationary_distrib...
- eoinmurray92 13y agoYou are correct, I was thinking of the master equation of a Markov process. In that case the eigenvalue of 0 gives the stationary distribution under a spectral expansion
- tlarkworthy 13y agoGot any links on that? Sounds interesting. Does that calculate its dynamic properties or something?