Skip to main content

Advertisement

Log in

POINTS OF SIGNIFICANCE

Markov models—Markov chains

  • This Month
  • Published:

From Nature Methods

View current issue Submit your manuscript

You can look back there to explain things, but the explanation disappears. You’ll never find it there. Things are not explained by the past. They’re explained by what happens now. –Alan Watts

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

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).

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Martin Krzywinski.

Ethics declarations

Competing interests

The authors declare no competing interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41592-019-0476-x

  • Springer Nature America, Inc.

This article is cited by

Navigation