• Corpus ID: 16071750

Interpretation and approximation tools for big, dense Markov chain transition matrices in ecology and evolution

  title={Interpretation and approximation tools for big, dense Markov chain transition matrices in ecology and evolution},
  author={Katja Reichel and Valentin Bahier and C{\'e}dric Midoux and Jean-Pierre Masson and Solenn Stoeckel},
  journal={arXiv: Quantitative Methods},
Markov chains are a common framework for individual-based state and time discrete models in ecology and evolution. Their use, however, is largely limited to systems with a low number of states, since the transition matrices involved pose considerable challenges as their size and their density increase. Big, dense transition matrices may easily defy both the computer's memory and the scientists' ability to interpret them, due to the very high amount of information they contain; yet… 

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