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Markov models—Markov chains

Nature Methods volume 16, pages 663–664 (2019)Cite this article

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Fig. 1: State transition models, transition matrices T, and the number of transitions required to approximate the steady-state limiting distributions, Tn (n→∞), to the displayed number of decimal places.
Fig. 2: Effect of the initial state (G, M) on the state evolution of 5,000 Markov chains with 20% and 40% chances of arrest.

References

  1. Skewes, A. D. & Welch, R. D. PeerJ 1, e127 (2013).

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Authors and Affiliations

  1. PhD candidate, Canada’s Michael Smith Genome Sciences Centre, Vancouver, BC, Canada

    Jasleen K. Grewal

  2. Staff scientist, Canada’s Michael Smith Genome Sciences Centre, Vancouver, BC, Canada

    Martin Krzywinski

  3. Professor of Statistics, The Pennsylvania State University, University Park, PA, USA

    Naomi Altman

Authors
  1. Jasleen K. Grewal
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  2. Martin Krzywinski
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  3. Naomi Altman
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Correspondence to Martin Krzywinski.

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Grewal, J.K., Krzywinski, M. & Altman, N. Markov models—Markov chains. Nat Methods 16, 663–664 (2019). https://doi.org/10.1038/s41592-019-0476-x

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